1 Introduction

Compared to mass production, in companies with an Engineer-to-Order (ETO) fulfillment strategy, typical activities such as design, engineering, project management, fabrication, and on-site assembly are only carried out after a customer order has been received (Strandhagen et al. 2019). Examples of such highly customized products are machines, plants, buildings or ships which are often produced in small quantities, with a low rate of order reappearance and on a project-by-project basis (Løkkegaard et al. 2022). In addition, supply chains in these ETO environments are often characterized by an off-site and on-site production part, which the on-site manufacturing taking place in a less controlled environment (e.g., construction site, shipyard, new and unfinished factory) that is subjected to instability and irregularities (e.g., changing weather conditions or customer requirements) (Braglia et al. 2019). These peculiarities of ETO result in a high level of effort in planning and coordinating all project and supply chain activities, often under budget and schedule pressure, resulting in a number of non-value adding activities and productivity losses that reduce competitiveness (Schulze and Dallasega 2021). As a result, contract manufacturers are seeking ways to remain competitive and improve efficiencies by re-evaluating their operations and adopting proven tools and strategies, as well as emerging technologies, to increase productivity and reduce losses (Sanders et al. 2016; Mayr et al. 2018b; Schulze and Dallasega 2020). The common productivity losses and wastes can be categorized according to the main phases of ETO projects (Schulze and Dallasega 2021). These include losses due to inefficiencies that are external to the project order, such as losses due to interferences with other trades (i.e., scheduling issues or upstream work not completed to specification) and losses due to customer wastes (i.e., frequent design changes or missing approvals). Losses due to inefficiencies directly attributable to the project include losses in engineering (i.e., delays or poor execution), in project management, (i.e., weak project coordination or not up-to-date schedules) in fabrication (i.e., delays or incomplete deliveries), and in on-site Installations (i.e., installation errors or safety breaches) (Schulze and Dallasega 2021; Braglia et al. 2022).

Previous studies have shown that the implementation of Lean principles and tools in companies with an ETO strategy leads to a reduction in waste and losses and an improvement in productivity (Sanders et al. 2016; Buer et al. 2018; Strandhagen et al. 2018; Schulze and Dallasega 2021). Lean processes and principles were originally developed in the automotive industry, which is characterized by serial production conditions such as stable demand for large volumes of related products (Jünge et al. 2021). Maximizing resource utilization by minimizing waste or non-value adding processes lays at the core of Lean Manufacturing (LM), which ultimately increases customer value (Jünge et al. 2021). Lean principles and methods can be applied not only in production, but also in indirect areas such as supply chain management (SCM), administration, design and planning, and project management (Paez et al. 2005; Sanders et al. 2016; Buer et al. 2018; Schulze and Dallasega 2020). However, implementing Lean practices in non-repetitive environments is challenging and fraught with many barriers (Buer et al. 2018; Schulze and Dallasega 2021) that could be overcome by incorporating emerging technologies from the fourth industrial revolution (Sanders et al. 2016; Schulze and Dallasega 2020; Braglia et al. 2022).

The fourth industrial revolution (or “Industry 4.0”) refers to the next stage of digitization of the manufacturing industry with technologies and concepts such as Internet of Things (IoT), simulation or cloud computing to create smarter factories and to realize low-volume, low-cost, and high-mix production (Buer et al. 2018). The combination of Lean and Industry 4.0 concepts has been discussed in the literature by investigating how Industry 4.0 can foster Lean practices (Buer et al. 2018), or by analyzing how Industry 4.0 technologies have empowering effects on Lean practices and the enabling effects of Lean on I4.0 in general manufacturing settings (Ciano et al. 2021). Furthermore, it has been examined how the combination of Industry 4.0 and Lean affects various performance dimensions of a production system (Sanders et al. 2016). However, links between Industry 4.0 technologies and Lean principles have not been formalized, especially for the industrial environment of ETO organizations, where Industry 4.0 application tends to be exploratory with little empirical evidence (Cannes and Gosling 2021) and the scientific works described as “sporadic, unorganized, and restricted” (Strandhagen et al. 2020).

The aim of this article is to fill these gaps by first analyzing and identifying which Lean practices and Industry 4.0 technologies are applied in practice for reducing common losses in companies with an ETO strategy. Secondly, it is validated whether these Lean methods and Industry 4.0 technologies used in ETO context are also described in the literature or not. The results are obtained by analyzing 16 companies from the construction industry, shipbuilding, and machine and plant manufacturing that apply both paradigms.

Our article contributes to both research theory and practice. It identifies research gaps in the literature in both applications and provides possible recommendations for managers. Limitations and further research directions are also presented. As such, this article contributes to the growing body of research discussing Lean and Industry 4.0 in the context of its application in the ETO industry.

The remainder of the article is organized as follows. Section 2 discusses related works, while Sect. 3 describes the research method. Section 4 presents the main findings of this study, while Sect. 5 discusses the results, identifies implications for research and future research directions. Finally, Sect. 6 summarizes and concludes the article.

2 Literature review

While the literature on Lean in repetitive production settings is abundant, it is only partially available for companies operating in a non-repetitive or less repetitive system, such as Engineer-to-Order (ETO), Manufacture-to-Order (MTO), and High-Mix Low-Volume (HMLV), which hinders the direct implementation of Lean principles and methods (Birkie and Trucco 2016; Adlin et al. 2020; Schulze and Dallasega 2020). This is emphasized by Tomašević et al. (2020) who found that managers and researchers presently face a “fragmented, unstructured, and unstandardized” existing body of research in the field of implementing Lean in non-repetitive manufacturing. Gosling and Naim (2009) point out that Lean strategies have been proposed in publications as a strategy for the ETO sector, but that a clear answer regarding their applicability is lacking. Similarly, Braglia et al. (2019) specify that while the number of publications discussing the adoption of Lean outside of volume production has increased, it is still challenging to implement LM principles in ETO organizations where the customer order typically dictates and initiates the design, planning and manufacture of the products. The literature reports individual cases where Lean tools, originally developed for low variance and high-volume production settings, such as Value Stream Mapping (VSM), Kanban, or Visual Management (VM), are also successfully applied in ETO context, characterized by high product variety and quantities often produced in batch-of-one (see Table 1).

Table 1 Results of the literature review
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Matt (2014) could apply an adapted VSM approach in an ETO environment to show general opportunities for improvement but emphasizes that it is challenging to quantify the effectiveness of the modified procedure due to missing meaningful data due to the project-related variations in times, workload, and inventory levels. VSM was used among other tools to reduce wastes in engineering design activities in ETO projects by applying enablers of Lean engineering design, but Lean implementation highly depends on cultural aspects (Jünge et al. 2021). Kjersem et al. (2015) could reduce the lead time and increase the throughput in a ETO-type shipbuilding case producing highly customized vessels with the help of ConWIP and Kanban, but emphasize that even though some benefits could be achieved, Lean tools remain hard to adopt due to the typical characteristics of ETO, such as project-based manufacturing, process uncertainty and the dynamic environment. Takt time production is introduced in a machine tool manufacturing, characterized by ETO strategy to increase production efficiency and improve lead times (Ricondo Iriondo et al. 2016). Bertolini and Romagnoli (2013) could successfully improve throughput rates, lead time, and product quality by implementing Lean tools VSM, one-piece-flow and continuous improvement processes (CIP) in an ETO manufacturer for its pre-assembly production, but the project remains a pilot. The Last Planner System (LPS) was successfully implemented in an engineering organization providing knowledge work to reduce project execution time, but improved KPIs have not yet been proven (Larsson and Ratnayake 2021a). Similarly, LPS and Location based Management System (LBMS) were used to couple on- and off-site construction to reduce wasteful storage and increase lead times, but the implemented approach was only a test (Dallasega et al. 2016). Using VSM and Gemba Walk, Hussain et al. (2020) cold introduce a single piece flow with a supermarket concept in a high-mix low-volume (HMLV) manufacturing plant thereby reducing wastes in the process, but remains limited to one case study. JIT has been introduced in a construction project to align the prefabrication with the assembly on-site thereby reducing losses, but stays confined to one use case in the construction sector (Rauch et al. 2015). Other Lean tools are occasionally applied with some success in project manufacturing environments, but lack widespread, standardized application.

Nonetheless, the literature is limited and there are only a few successful empirical case studies focusing on effectively reducing conventional losses in companies with an ETO strategy (Birkie and Trucco 2016; Schulze and Dallasega 2020). Adlin et al. (2020) systematically analyzed the literature on the adoption of Lean Manufacturing in small batch size manufacturers in high-cost countries (SBSM) and found that there are few empirically validated studies in the literature on how to implement LM in HMLV manufacturing. The authors emphasize that LM must be adapted to local circumstances and aligned with other practices used in the context, such as Enterprise-Resource-Planning (ERP) systems, product modularization or project management practices. Djassemi (2014) points out that while small manufacturing shops characterized by HMLV, and one-of-a-kind (OKP) production are important contributors to any economy, little is published on related Lean practices and successes in such environments. In general, more empirical research is required to demonstrate and prove the benefits of Lean to improve the efficiency of operations in ETO companies (Gosling and Naim 2009; Birkie and Trucco 2016). According to Birkie and Trucco (2016), no evidence has yet been found to support the applicability of Lean in the ETO space. Similarly, Ricondo Iriondo et al. (2016) point out, that that there is only anecdotal evidence of Lean Production implementation in the custom machine tool industry, although manufacturing efficiency is key maintaining competitiveness.

Various researchers (Buer et al. 2018; Strandhagen et al. 2018) indicate that further research should focus on emerging technologies as a way to mitigate analyzed sources of waste and productivity losses. Currently, technologies and concepts from Industry 4.0 have emerged as a compelling paradigm to optimize processes and other methods and tools from the Lean manufacturing environment (Buer et al. 2018), but digitalization efforts in in the ETO environment has not yet been sufficiently addressed (Mayr et al. 2018a). Cannes and Gosling (2021) report that Industry 4.0 is a forthcoming theme to support ETO but is currently described in the literature in a rather exploratory manner with less evidence and more focus on “characterizing, categorizing, illustrating and defining particular phenomenon”. They conclude that future research should analyze how Industry 4.0 technologies can improve SCM in ETO. Similarly, Strandhagen et al. (2020) point out, that the literature on the application of Industry 4.0 technologies in ETO remains sporadic, disorganized, and restricted.

However, various I4.0 technologies have already been applied in project manufacturing to reduce losses. IoT-enabled sensors, such as RFID were applied to better track and coordinate the off- and on-site production of construction components for an ETO supply chain (Dallasega 2018) or to track the status update of finished material (Pero and Rossi 2014; Oluyisola et al. 2018), but remain individual use cases. Big Data analytics is important to JIT production control (Mayr et al. 2018a) as collected data in real-time can be used to adapt schedule and increase productivity even in HMLV environments (Dequeant et al. 2016), however, these proposed solutions have not been tested. 3D Printing has the potential to be used for manufacturing single components on-demand according to exact customer specifications, but has not yet been widespread implemented in ETO environments (Jha 2016; Oettmeier and Hofmann 2016). Digital Twin, as a controlling instance of their physical counterparts allow for bidirectional information flow and can thereby support decision making in Project environments such as shipbuilding (Jagusch et al. 2021) or help to reduce downtime and inefficient maintenance processes by supporting Prescriptive Maintenance and PPC in manufacturing lines (Padovano et al. 2021) but both examples remain concepts. Augmented Reality (AR) has been proposed to support operators for assembly tasks (Strandhagen et al. 2020) and Virtual Reality (VR) can be used for digital mockups of future workspaces to optimize work stations for operators before being actually built (Arkouli et al. 2021). Similar, collaborative robots have been suggested to support physical tasks in assembly and thereby increase productivity and facilitate handling (Malik and Bilberg 2017; Kocsi et al. 2020; Arkouli et al. 2021). However, these proposed frameworks and solutions have rarely been tested in actual ETO environments and require further practical investigation. Industry 4.0, in contrast to the IT, automotive or consumer industries, is only at the beginning of a further application in the ETO area (Vellmar et al. 2017).

The literature reviewed shows a few successful examples where Lean or I4.0 practices have been used in project manufacturing environments to mitigate common losses. However, many case studies are often single cases, or were only tested in a pilot project. Accordingly, there is a lack of broad empirical studies that show how losses can be minimized in practice in organizations with an ETO fulfilment strategy. References in the literature were made to the Lean tools VSM, VM, Kanban, CIP, cycle planning, LPS, LBMS, Poka-Yoke and JIT, as well as the I4.0 technologies Digital Twin, AR, VR, and collaborative robots. However, there are many other practices in research that were not found in the literature search to be related to project manufacturing. In this respect, there is a need to investigate which tools and technologies are really used in practice to reduce losses at project manufacturers and whether they are also the subject of scientific investigations.

This article is therefore intended to help close this gap further by addressing the following research questions:

RQ1: Which Lean methods and I4.0 technologies and concepts are used in practice by companies with an Engineer-to-Order strategy to reduce common losses?

RQ2: Are there certain practices from Lean and Industry 4.0 that are applied in practice in companies with an ETO strategy that are not discussed in the literature and vice versa?

Based on the research questions, the following sections discuss the outcomes and analysis of the literature review and empirical investigation.

3 Research methodology

3.1 Research design

For this study, an explanatory sequential mixed-method design was applied. This embedded design consists of collecting qualitative data (via literature review) to explore a phenomenon and quantitative data (via a survey questionnaire and semi-structured interviews) to explain the relationships found in the qualitative data (Subedi 2016).

Based on the loss categorization described in the introduction, we wanted to find out what Lean and Industry 4.0 practices companies with an ETO fulfillment strategy apply to mitigate conventional losses that occur in typical project-based manufacturing. Therefore, we first conducted a literature review to analyze the scientific works on this topic. Second, to collect empirical data we conducted a survey questionnaire and qualitative semi-structured interviews. Survey methods are used to collect primary data from participants, while semi-structured interviews are applied to gather qualitative data which allow exploration of subjective experiences, understanding, and personal beliefs (Mathers et al. 2013; Bray et al. 2014).

A literature review was first conducted to determine the current state of Lean methods and Industry 4.0 technologies application to mitigate conventional losses in companies with an ETO production strategy. We performed a keyword search in the most important electronic database (Elsevier’s Scopus) (Orzes et al. 2019) which is also one of the leading databases of scholarly impact to search the publications connected with the analyzed topics supplemented by an ensuing forward and backward search. The search strings to find papers were constructed through the combination of the BooLean operators “or, and” among the various keywords.

As several expressions for engineer-to-order strategies are used in the literature, we applied TITLE-ABS-KEY (“Engineer-to-Order” OR “ETO” OR “high-mix low-volume” OR “HMLV” OR “contract manufacturing” OR “project-based manufacturing” OR “One-of-a-kind” OR “Mass customization”) as the first search term, combined with AND TITLE-ABS-KEY (“Lean” OR “Lean manufacturing” OR “Lean production” OR “Lean construction” OR “Lean management”) as the second term for Lean. The performed search in the Scopus database resulted in 213 identified papers. Similarly, several expressions are used in the literature referring to Industry 4.0, which is why we combined the same search terms used for Engineer-to-Order with AND TITLE-ABS-KEY (“Industr* 4.0” OR “I4.0” OR “emerging technologies” OR “smart manufacturing” OR “digital manufacturing” OR “digitalization”) as the second term for Industry 4.0. The performed search in the Scopus database resulted in 50 identified papers.

The articles were then analyzed for significance using filter criteria and afterwards screened based on (i) title and (ii) abstract followed by (iii) full text. Exclusion criteria were applied at this stage to select only the more significant studies to include in the review. These include (i) studies published since 2010 to include more relevant scientific work as well as (ii) studies published in peer-reviewed journals and conference proceedings. By restricting the search to only peer-reviewed journals and conference proceedings, the quality control of search results can be improved due to the meticulous process that papers published in such journals undergo prior to publication (Colicchia and Strozzi 2012). Further, the search was limited (iii) to papers written in English. Additionally, (iv) duplicates were removed. The final sample consisted of 61 papers of the search for Lean and ETO, and 24 papers of the search for Industry 4.0 and ETO.

After reading titles and abstract of the identified articles, several papers were removed once they deemed not fit for the research scope or were duplicates. Ultimately, 24 papers were left for further analysis after applying the same exclusion criteria described above.

3.2 Sample selection

To collect empirical data, companies with an ETO order fulfilment strategy were contacted to participate in the survey and interviews. The following criteria were applied to select the companies. The sample should be representative of the ETO sector by choosing companies with different characteristics such as small, medium and large companies as well as companies from different manufacturing industries. Therefore, typical ETO sectors such as construction, shipbuilding, and machine and plant manufacturing also called machinery-building, machinery or machine and equipment manufacturing were chosen for this study since they are major industries of the EU and industrialized countries and contribute a significant share to the industrial GDP (Pacheco-Torgal 2014; European Commission 2020). And second, the companies should operate in different countries to receive information and perspectives from different cultures and countries. Furthermore, the companies should apply Lean and I4.0 practices.

Since companies with an ETO strategy often develop and produce highly complex products with sensitive data, very few are willing to share confidential information. Therefore, non-probability sampling was used in this research, making it exploratory and the findings preliminary (Malhotra et al. 2017). To select the companies to be questioned, purposive sampling was utilized as this non-random technique allows respondents to be explicitly selected based on the necessary information they can provide on the concepts and topics at question as well as the willingness to participate in the study (Campbell et al. 2020). Additionally, purposive sampling helps to better match the objectives of the research with the sample, thereby increasing the rigidity of the study and the reliability of the data and results (Campbell et al. 2020). Some of the requested companies, despite their willingness to participate in the study, could not be included in the final selection because they apply e.g., Lean but not I4.0 practices or vice versa.

All companies that participated in this study are listed in Table 2 with code names as to protect their identity. A total of 16 companies with an ETO strategy from construction (8 companies), machine and plant manufacturing (4 companies) and shipbuilding (4 companies) were selected. The distribution shows an inequality between the different ETO sectors. Originally, the distribution was supposed to be 8 companies for each sector in order to achieve better comparability. One reason for this was the discretion of the shipbuilding companies, which frequently turned down requests to comply with trade secrets and their involvement in military contracts. Another reason was the difficulty in finding suitable machinery building companies with an ETO order fulfillment strategy that hat sufficiently applied both Lean and Industry 4.0 concepts. In addition, it was easier to identify and contact the construction companies, as they are often organized in relevant associations such as the “Lean Construction Group Italy” or similar.

Table 2 Sampled companies
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The companies come from northern Europe (e.g., Norway), central Europe (e.g., Germany), and southern Europe (e.g., Italy). One half of the sample companies are small and medium sized enterprises (SMEs) with around 60 to 500 employees and annual sales between €10 million and €500 million. The other half are large companies with more than 500 employees and annual turnover between €700 million and €4.6 billion. The contacted companies assigned us the people responsible for the survey and interviews who were commissioned with topics Lean and Industry 4.0 in their respective organizations. Respondents were typically the appropriate "Lean Experts" or "Lean Managers" in their organization or held equivalent positions, such as “Production manager” or “Head of digitization and innovation management”, occasionally also the respective high-level business executives of the company. Respondents' professional experience ranged from 5 to 28 years.

3.3 Survey questionnaire design

A structured survey questionnaire was used to gather data on the application of Lean tools and Industry 4.0 technologies to mitigate losses in organizations with an ETO strategy. The main objective of the survey is to aggregate empirical data to solve the research problem.

Therefore, the questionnaire developed for this study consists of different parts, including: (A) background information about the respondents and the company itself, (B) list of loss categories during an ETO project, (C) the Lean methods and tools applied, (D) the Industry 4.0 technologies applied. Useful information about the study is mentioned in the header of the questionnaire. At the end of each section there is some space for the interviewees to provide comments or additional information if desired. The design of the questions was kept simply, yet easy for the respondents to understand. Once the structure and questions has been defined, this instrument was validated against the criteria by experts from various firms with an ETO strategy, who assessed and scored the entire questionnaire. Any corrections and suggestions were implemented accordingly.

3.4 Data gathering

Data collection was primarily based on a series of semi-structured interviews supported by the survey questionnaire. Archival data (e.g., annual reports, websites, and internal documents on Lean or Industry 4.0 implementation projects, job descriptions or project reports, shared during site visits) were also used to triangulate the empirical evidence by cross evaluating via content analysis the results from the survey and semi-structured interviews with the documents to check whether similar findings occur. The survey and interviews were conducted over a period of six months (from November 2021 to April 2022).

3.5 Semi-structured Interviews

Individual interviews were conducted in a semi-structured form. As both a data collection strategy and a qualitative research method, semi-structured interviews (SSI) intend to establish and verify the participants' perspective in order to confirm, correct or realize new knowledge related to the research focus (McIntosh and Morse 2015). The companies listed in Table 2 were contacted and an appointment was made for the interview. The questionnaire was sent to the responsible interviewees and completed by them in advance. After the questionnaires were returned, they were evaluated, and a corresponding protocol was prepared and returned for validation. After that, the date for the interview was set. Part of the interviews could be conducted directly on site at the company. The other part was conducted online via video conference due to the pandemic constraints. The interviews, which lasted approximately 1 ½ hours, were conducted by the two members of the research team either in person at the interviewed company or over the internet via videoconference, depending on the preference and location of the participants. All interviews were audio or video recorded with consent of the participants. The recordings, as well the use of rigorous case protocols, contributes to the reliability of our investigation.

3.6 Data evaluation

After the interview, the collected data were summarized in a protocol and sent back to the interviewees for validation. The validated protocols and questionnaires were then summarized and analyzed. The responses received were compiled into an Excel spreadsheet and the data analyzed. Data from the interviews were cross-checked with information from the survey questionnaires, archival data, and on-site observations to ensure internal validity (Yin 2009). External validity was ensured by integrating ETO companies with different characteristics (e.g., industry, size) into our study. Corresponding tables were created based on the loss categories and the Lean and Industry 4.0 practices identified from the literature to mitigate them. These results were then compared with the practices found in the questionnaires and interviews. In this way method triangulation, by employing different types of qualitative research approaches (e.g., survey, interviews, document analysis) and data triangulation using of multiple data sources (e.g., primary data and secondary data) were employed to reduce biases and improve validity of the study. The results and the corresponding tables are explained in the next chapter.

4 Results

This chapter summarizes the findings of our research in two tables, addressing our research questions.

4.1 Occurrence of Lean methods and Industry 4.0 technologies in practice and in theory regarding the ETO context

Table 3 presents the Lean practices and Industry 4.0 technologies identified in the literature that are applicable to mitigate the common losses in companies with an ETO order fulfillment strategy according to the classified loss categories. The table also indicates which of the interviewed case companies uses each Lean method in their organization.

Table 3 Applied Lean methods and industry 4.0 technologies in case companies and in the literature according to common loss categories
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In the first loss category—Losses caused by obstruction with other trades—the Lean tools used by the surveyed companies were Last Planner System (LPS), Location Based Management System (LBMS), Pull scheduling method, and Takt Planning. The LPS was mostly used among the construction companies since it is a Lean Construction (LC) tool, but it was also used by the shipbuilding companies to coordinate and schedule the interfaces between the individual trades. For example, case company S, a shipbuilder, uses LPS in a portacabin located on the deck to coordinate all assembly tasks between the internal crew and external trades as close as possible to the assembly site. Case companies B, C and D use LPS as the basis for planning and scheduling at all their sites to plan activities in detail.

Only the Industry 4.0 technologies and concepts of Cybersecurity and Horizontal Integration are applied by the ETO companies interviewed in relation to the first loss category—Losses caused by obstruction with other trades. Most of the case companies surveyed had some form of Horizontal integration with their suppliers to collaborate across companies in material supply and scheduling. Case company R sees itself as a system integrator who carries out planning integration services in the production and assembly of components which come from very closely integrated suppliers. To this end, the company uses a portal to integrate suppliers and other trades. Shipbuilding companies are also very concerned about protecting their data through Cybersecurity measures.

The Lean methods applied in the second loss category—Losses caused by customer inefficiencies—such as Integrated Project Delivery (IPD), Detailed Briefing, and Concurrent Engineering (CE), were all encountered in practice but not specifically mentioned in the literature in the context of ETO. Case company B, for example, uses IPD in the pre-construction phase to optimize the project structure, cost and budget allocation together with the customer. Case Company E, on the other hand, uses IPD in pilot projects with the aim of later pushing for a company-wide introduction. The firm sees IPD as a key in the construction industry because it brings together all parties involved in the project. However, case company Q brings forward that while IPD brings great benefits, it is still a new topic in the ETO sector. The Lean tool CE is used by shipbuilding companies Q, R, and T to reduce uncertainty and shorten the overall throughput time of their projects by running design and engineering activities in parallel and cross-functional teams.

In the second loss category, none of the companies analyzed uses Building Information Modeling (BIM) or Cloud Computing to reduce customer-caused losses. The construction companies surveyed emphasized that end customers and planners are only insufficiently involve in their construction projects and often not use BIM at all or only insufficiently.

Lean practices to reduce losses in the third loss category—Losses caused by the engineering department—were partly found in practice and in the literature. Value Based Management (VBM) was only applied by case company B, who uses it at the beginning of the design phase to define the value for the client. Value Stream Mapping (VSM), on the other hand, is mainly applied by case companies from the construction and shipbuilding sectors. Case company J, a machine and equipment manufacturer, applies VSM as one of the few Lean tools to map the major value streams on the shop floor. Interestingly, case company B applies VSM in the administrative area such as purchasing, warehousing, invoicing and costing to identify and reduce non-value adding activities in the non-production areas. Virtual Design Construction (VDC), Target Value Design (TVD), and Design Structure Matrix (DSM) were only encountered a few times in the interviews to mitigate losses in the design and engineering department by establishing a structured process for engineering tasks, but not in the literature. Design workshops are also applied in a few case companies, often but not always regularly.

Regarding the third loss category—Losses caused by the engineering department—Simulation, in form of Product and Process Simulation as well as Digital Twin (DT) are applied by the companies interviewed. Case Company L has implemented a DT with over 180,000 measuring points for their machines to enable real-time monitoring, optimization, maintenance, and remote access of their machines sold to end customers. In contrast, case company D is testing various DT systems which can be used with smartphones and an accessory tool that enables precise localizations in space on-site. Case Companies E and B use BIM to simulate their construction and site logistic processes, while case company L is using DT to simulate its machines to optimize and improve design. Although BIM is arguably the most important Industry 4.0 technology for the construction sector, especially in building construction, only a handful of the companies interviewed apply it in their operations. Case company D mentions that currently not all required functions can be fulfilled in BIM such as legal issues, required level of development (LOD) specifications and a common data environment. However, the trend is that BIM is increasingly being used by private developers and only in recent years have planning offices, consulting firms and design engineers also started using BIM. However, case company A reports that its clients are not able to manage data and information transfer despite using BIM. Case company C adds that while planners could use BIM, it would sometimes make them redundant. Case company D applies BIM models of the buildings to be constructed for schedule coordination to manage all scheduling and logistics processes. Even for new construction projects, 3D modeling is rarely used due to a lack of knowledge about the life cycle of the building and the possibilities that arise from the data.

Regarding the fourth loss category—Losses due to project management inefficiencies—the ETO companies surveyed have applied Lean practices such as Work structuring and scheduling, Conference Management, as well as LPS and LBMS in their operations to reduce losses caused by project management inefficiencies. Work structuring is used by the interviewed companies to create a reliable and responsive workflow by aligning the critical project processes. Conference Management is applied only by one case company to allow structured implementation and logging of meetings between the different project participants.

Only Cloud Computing is utilized by most of the companies examined in the fourth loss category—Losses caused by the project management department. Especially, the construction and shipbuilding companies interviewed use Cloud Computing in project management processes to share important data in real-time and to involve all project stakeholders in decision making. For example, case company F uses Cloud Computing for all production-related documents to be uploaded and shared amongst the operators and managers. But security concerns are an issue. For example, shipbuilding company R does not store product drawings or sensitive data in the cloud. Other companies, such as case company G, use Cloud computing only partially for certain established processes, such as the exchange of error and maintenance reports.

The losses in the fifth loss category—Losses caused by fabrication inefficiencies—have been encountered both in the literature and in practice with the Lean tools Standardized works, Poka-Yoke, and Just-In-Time (JIT) concepts. JIT and Kanban are used by construction company B, mainly in timber construction, where processes are easier to plan, and quantities are better known. JIT has also been applied by case company G, where components are delivered JIT (in hours) to the machines on the shop floor. Poka-Yoke has only been applied by a few companies interviewed in different scenarios to reduce errors in the production or assembly processes. Case Company J has difficulty implementing Poka-Yoke due to the many variants of components and products. In their particular case, a Poka-Yoke solution would need to be constantly replaced on the machines. The most commonly used tool in this category was Standardized Works which is utilized equally by all ETO categories surveyed.

IoT, Vertical Integration, Big Data and Artificial Intelligence (A.I.) as well as Augmented and Virtual Reality (AR and VR) are the most commonly applied Industry 4.0 technologies to mitigate losses in the fifth loss category—manufacturing-caused losses. Among the interviewed construction companies, sensors and IoT systems are used for equipment tracking and maintenance purposes (case company A), tracking of their modular prefabricated components (case company E), and RFID and QR-Codes for component tracking (case company B). Machine manufacturing company I, on the other hand, has difficulties using sensors in its assembly area, the alpine environment, due to often extreme weather changes, lightning strikes, and snow. Among the analyzed shipbuilding companies, IoT is used in forms of sensors, RFID, and GPS to track load carriers (case company R), or sensors to collect data for maintenance information and information processing for the end customer (case company K). Additionally, sensors are applied to monitor process conditions such as air temperature and humidity, as well as the condition of machines and systems since several manufacturing processes are critical in terms of environmental conditions such as temperature or humidity (case company R).

As far as the sixth loss category—Losses caused by on-site assembly or installation—is concerned, some Lean tools were only encountered once or twice in practice, e.g., Total Quality Maintenance (TQM), Total Productive Maintenance (TPM), and Six Sigma. First-Run studies and Benchmarking were hardly used in practice by the companies surveyed. Daily Huddle Meeting was only employed by two construction companies examined (company B, C). JIT and Kanban are used on-site by construction and shipbuilding firms, while Poka-Yoke was applied by firms from all three ETO categories researched. As an example, Kanban and JIT are used in prefabrication at case company R with increasing penetration to ensure a timely delivery of materials without the need for excessive on-site storage space. Case company G delivers its components Just-In-Time to its machines. Poka-Yoke, for example, is used by case company R to prevent assembly mistakes during cabin assembly on-site.

5S and Visual Management (VM) as well as Gemba Walk are mainly applied by construction and shipbuilding companies to investigate the source of occurring issues on-site. For example, case company B applies 5S daily on the construction site and additionally once a month an audit of the construction site by the respective site manager. On the other hand, case company G uses VM tools such as One-Point-Lessons not only on-site but in all departments of the organization. Prefabrication and Modularization as well as Standardization are both primarily used by construction and shipbuilding companies. Although these methods are relatively common in practice, especially in construction, they are rarely found in the analyzed literature. Case company R has introduced modular construction and Prefabrication for many components in its assembly. Case company S utilizes templates to standardize workflows in production. Kaizen or Continuous Improvement Process (CIP) is the most commonly applied Lean tool in this loss category in the ETO companies studied. Company R uses a structured CIP process in which improvement actions in individual departments are initiated by employees. Accordingly, Lean projects are created and sustained with the CIP approach.

Virtual Reality (VR) has been used in case company B, a construction firm, for customer communication and planner meetings and in case company R, a shipbuilding firm, for more than ten years in product development. In case company K, a machine manufacturing company, VR is used for on-site maintenance and assembly support, especially by untrained personnel.

Augmented Reality (AR) is applied among the analyzed construction companies for design reality comparison in building services (case company B), for various tasks in its MEP construction projects (case company H), and gradually for site assembly to get remote support for specific problems on-site (case company G). Machinery building company L uses AR by guiding end customers through the machine on site with AR glasses to carry out maintenance work. In contrast, shipbuilding companies Q, R, and T report that AR application has not caught on because most models and drawings are 2D-based or not detailed enough in 3D for a meaningful application. “AR is not yet an optimal solution to easily visualize data, the accuracy is not right yet, and data protection does not work” as interviewee R puts it. The interviewee emphasizes that the implementation of AR in shipbuilding fails due to technical hurdles, such as the lack of simple data visualization, lack of accuracy and strict operational data protection. Case company K has a ‘paperless’ production. Using screens at assembly stations, employees access all drawings and information for their specific orders via a specific assembly information system via the cloud and report back all orders. Case companies B and C, construction companies also testing various autonomous robots, especially in timber construction, less so on traditional construction sites, to save time and personal on repetitive tasks but there is still a lack of widespread implementation.

Additive manufacturing is only marginally described in the literature related to ETO, but is used by a shipbuilder and machinery builder, who use 3D printing in the test department for prototyping. Case company T uses Additive manufacturing to print templates for assembling doors and hatches, which are used as assembly aids as well as a Poka-Yoke solution.

Vertical integration is used by several of the companies surveyed. For example, case company I has machines that are networked with Manufacturing Execution System (MES) that communicate with ERP systems. Similarly, case company J has automatic feedback through the ERP system from pre-assembly to main assembly, saving time and enabling real-time data exchange.

Big Data and Artificial Intelligence (A.I.) are utilized by several case companies to support decision making and improve the adaptability of DTs to dynamically varying boundary situations (case company L). In our research, case company J is already diligently collecting user data for its products and could use Big Data for evaluation, but the question is how to evaluate the data and what benefits it will bring. In this line, case company Q, J, and T mention the potential of Big Data evaluation, but there is a lack of specialists who can evaluate and analyze the collected data correspondingly.

Among the companies surveyed, Cloud Computing was the only applied Industry 4.0 technology in terms of reducing losses due to on-site assembly. Case company E uses an app and cloud computing to manage defects and reports on site. Case companies R and S only store data on the cloud that does not describe the product in order to protect their sensitive data.

5 Discussion

This section discusses the findings of our research with respect to each of the research question and examines their limitations. Furthermore, implications for research and practitioners are outlined. Future research directions are also proposed.

5.1 Losses due to obstruction by other trades

As the survey findings indicate, the Lean tools LPS, LBMS, Takt Planning, and Pull Scheduling are mainly applied to reduce common losses due to obstruction with other trades. Even though the LPS and LBMS are both tools from Lean construction applied by the interviewed cases, we have found that in addition to contractors, shipbuilders also apply LPS to reduce losses caused by obstruction with other trades. Nevertheless, only a fairly small focus on LPS implementation in non-construction companies is currently encompassed in the literature. Larsson and Ratnayake (2021a) apply LPS in an ETO engineering organization to facilitate the planning and control of project activities focused on knowledge work, such as engineering activities or design tasks. This may explain why LPS is still mainly applied in construction companies, despite its inherent benefits for improving on-site collaboration and schedule reliability (Dallasega et al. 2016). Similarly, LBMS is not widely applied by the interviewed companies because the tool is not supportive of Just-In-Time (JIT) and therefore has limited use in synchronizing the supply chain between manufacturing and on-site construction (Dallasega et al. 2016). Takt planning was only used by one construction company to batch their pre-production for the construction sites. It is surprising that none of the customized machine building companies in the study used this method, even though it is a central pillar applied in Lean Production systems to reduce lead times and stabilize work processes. The concept of Pull Scheduling for the ETO context has also been mentioned in the literature as a way to mitigate losses caused by obstruction from other trades. Hentschke et al. (2019) points out that pull enables the manufacturing of goods that are pulled by the customer order, which in turn increases the flexibility and transparency of production and reduces lead time. This was also mentioned by the companies interviewed who emphasized the added value of better planning of overarching activities. Adlin et al. (2020) emphasis that the implementation of pull and flow in small batch size manufacturing is an incremental process that takes time.

BIM, as a key Industry 4.0 technology for the construction industry is not used by any of the surveyed cases to reduce losses due to other trades. Also, in the literature reviewed, the focus of BIM applications is in the construction sector and not in other ETO areas. The use of BIM and GIS to collectively display material status throughout the supply chain is mentioned by Dallasega (2018). Further, the author reports that BIM currently targets primarily the design and pre-construction planning phases and can be used for planning the construction supply chain. BIM also does not play a role in the shipbuilding companies interviewed, as the main drawings are all still created in 2D, which means that closer links with suppliers and subcontractors in the shipbuilding industry will continue to be difficult. However, Horizontal Integration is used in different ways by the companies surveyed to integrate other trades, suppliers, and subcontractors. Strandhagen et al. (2020) mentions the use of Industry 4.0 technologies that enable holistic data exchange in real-time between different departments and suppliers, but there is a lack of further meaningful literature on this topic with reference to contract manufacturing. This is evident, for example, in the high fragmentation of the construction industry, where long-term cooperation are scarce (Tezel and Aziz 2017). This was also confirmed in the interviews with the construction companies, who find it difficult to promote horizontal involvement beyond their own organization.

This is also evident in the area of cybersecurity. Even though one third of the case companies interviewed apply Cybersecurity in some form, there seems to be a lack of practical guidance in the literature for the ETO area. Companies in the HMLV and ETO environment often produce highly complex and innovative products specifically to meet customer requirements, which means that much of the contract value is generated in the design and engineering phase. Therefore, greater attention should be paid to securing their digital infrastructure and sensitive data with the right Information and Communication Tools (ICT) and cybersecurity technologies. Project manufacturers with data protection needs should turn to professional IT providers to implement cybersecurity solutions that meet their needs.

5.2 Losses due to inefficiencies by the customer

The analyzed cases mainly use Lean practices such as IPD, Detailed Briefing, and CE to deal with customer generated losses, even though they were not mentioned in the literature. None of the companies surveyed use I4.0 technologies such as BIM or cloud computing in this respect. Dallasega (2018) mentions that the use of BIM and Cloud Computing efficiently integrates data from suppliers, carriers, and subcontractors in construction supply chains, which enables them to share information in real-time. Interviewee C mentioned that IPD, for example, is rarely used in construction, even though it is an important tool that brings all project stakeholders together. This could indicate that the construction industry is still very fragmented and collaboration at the vertical level is rare (Tezel and Aziz 2017). Case companies B and E explained that IPD conflicts with many procurement laws for public projects and is therefore often opposed by owners and contractors alike. This could explain why IPD is rarely applied in practice and not often mentioned in the literature. Here, the literature is lacking lacks up-to-date and practical research that could be used by managers in companies with an ETO strategy to deal with customer-related inefficiencies.

5.3 Losses due to inefficiencies in the engineering department

Lean tools and methods to address losses caused by the engineering department, such as VDC, TVD, DMS, and Design workshops, were also partially used by the interviewed companies, but not discussed in the literature. This is because these tools are often used in the construction sector, since they were developed accordingly in the context of Lean Construction, and the relevant literature can be found mainly only there (Babalola et al. 2019). Although DMS, TVD, and VDC are typical Lean tools applied mainly in construction, we found them to be applied in all ETO sectors of our study. Still, there is a lack of evidence-based studies in the literature to enable the diffusion of these tools in other areas of ETO manufacturing. The concept of Value based Management (VBM), present in only one of the interviewed case companies but not mentioned in the analyzed literature, aims at aligning all processes to maximize the value of an organization, but adequate concepts for applying VBM to SCM, let alone for combining VBM with ETO, are lacking (Young et al. 2000). This concept is often referred to interchangeably with VSM in the literature (Babalola et al. 2019), which could be one reason why this tool is almost not applied at all.

An exception is Value Stream Mapping, which seems to be one of the most prominent Lean tools applied by the analyzed companies with an ETO strategy to address the losses caused by the engineering and fabrication department. In analyzing the adaption of Lean tools and principles in job shops of small HMLV manufacturers, Irani (2011) found that VSM, for example, is not suitable for use in HMLV environments with hundreds of unique product mixes and routings because VSM is not capable of mapping multiple interacting value streams. On the other hand, articles from Breitenbach and Ferreira (2014) and Djassemi (2014) show the meaningful use of VSM in a custom equipment manufacturer (ETO) and small manufacturing shops that helped identify sources of waste and non-value-adding activities within the organization. In their review of Lean literature for Small Batch Size Manufacturers (SBSM), Adlin et al. (2020) found that VSM emerges as the most commonly applied Lean practice. However, a contract manufacturer’s individual situation and requirements are critical in determining whether VSM can be used appropriately. This was also confirmed the case companies we studied, which attested to VSM’s often limited applicability in their organizations.

Among the applied I4.0 technologies, Product and Process simulation and Digital Twin (DT) are applied by a few case companies to reduce their losses in the engineering department. Notably, the concept of DT is sparsely discussed in published research in companies with an ETO strategy. Schlette et al. (2020) used DT to program and automate assembly tasks for an autonomous robot in an HMLV manufacturing setting. Padovano et al. (2021) used DT to facilitate decision making for an integrated Production planning control (PPC) and prescriptive maintenance (PsM) system in an MTO/ETO manufacturing environment. Both studies are rather concept-based and lack validated real-world examples.

5.4 Losses due to inefficiencies in the project management department

Similar to the first loss category, LPS and LBMS were the most frequently mentioned Lean tools for managing losses in the project management department. Both tools help monitor processes using various scheduling techniques or linking locations and corresponding activities. Interestingly, Work Structuring and Scheduling was mentioned more periodically by the project-based companies interviewed, but no source in the academic literature discussed this Lean method. The reason for this could be that this tool was developed specifically for the construction industry. Only Babalola et al. (2019), in their review study of applied Lean practices in the construction industry, found that this tool is used by a few construction companies. Among the interviewed cases, only Cloud Computing is the only I4.0 technology applied to improve project management processes. Cloud Computing is used by sharing relevant and up-to-date information in real-time between the project’s stakeholders thereby also improving existing Lean tools such as LPS.

5.5 Losses due to inefficiencies in the fabrication department

On the other hand, all three Lean tools – Standardized works, Poka-Yoke, and Just-In-Time – to reduce losses in the fabrication department were applied by the respondents and found in research. Even though JIT is a frequently discussed topic in the researched literature, it is emphasized that its implementation in the ETO production setting is very difficult because of the need for very accurate demand forecasting and flexible processes, particularly fast set-up times (Bortolotti et al. 2013). However, the literature reports successful cases where JIT was used to achieve a pull strategy using Kanban cards on Lean construction sites (Dallasega et al. 2016; Bajjou et al. 2017; Tomašević et al. 2021). Wang et al. (2021) analyzed how adopting the JIT strategy for inbound logistics in cruise ship construction can reduce costs. Poka-Yoke or error-proofing is only applied by a handful of the companies interviewed, mainly from the construction and shipbuilding sectors. Irani (2011) mentions that Poka-Yoke is applicable in a job shop of HMLV manufacturing. Similarly, Babalola et al. (2019) reports that this Lean method is commonly applied in construction. Standardized Works is mentioned only once in the literature in the context of ETO, although it is applied by many of the firms in this study. There still seems to be a need to scientifically investigate successful applications in an ETO context. Poka-Yoke, on the other hand, is much trickier to implement due to the customization of products, as the cases analyzed reported.

More I4.0 technologies, such as IoT enabled devices, AR and VR, 3D Printing, Big Data Analytics and even autonomous robots are being applied by the interviewed cases as described in Sect. 4. IoT-enabled Sensors and RFID are mentioned amply in the literature in the context of ETO, often in context of Vertical Integration. For example, Grube et al. (2017) used IoT in form of RFID and Cloud Computing to digitize order handling and traceability in small businesses. The authors highlight that RFID is an important enabler for IoT in the case of SMEs. Strandhagen et al. (2020) mention the use of sensors in products and components to create an industrial IoT for extending value chains, which could be used to handle end-of-life phases of ships. Similarly, Pero and Rossi (2014) use RFID technology in a case study of an ETO manufacturer to increase the visibility of components, operators, and machines in an ETO supply chain. A similar application of RFID in an ETO environment is also researched by Oluyisola et al. (2018).

Autonomous or Collaborative Robots (Cobots) are discussed in the literature for an ETO setting, but only one interviewed company applies robots only for testing and very simple applications. Arkouli et al. (2021) analyzed the use of cooperating robots for manufacturing of large-scale parts in HMLV environments and mentioned that aspects such as safety, autonomy, and performance need to be thoroughly investigated. The concept of collaborative robots is mentioned more frequently but not encountered in practice. Malik and Bilberg (2017) proposed a Lean automation approach for implementing collaborative robots in manual assembly in HMLV production. Further case studies are needed to understand and measure the benefits of applying autonomous robots in project-based manufacturing operations. The interviewed manager of case company B also mentions the lack of qualified personal and explains that “Industry 4.0 knowledge that has already been collected but remains in one area and is difficult to extend to other areas of the company”.

Big Data and Artificial Intelligence (A.I.) are utilized by some case companies and these concepts are discussed in the literature. Strandhagen et al. (2020) mention that Big Data analytics and A.I. can support decision making and, in conjunction with sensors in products, information obtained can be analyzed and optimized for future energy-efficiency designs. Fox and Do (2013) report on using Big Data for monitoring and reporting of performance use in the shipbuilding industry, but also mention various challenges in implementing Big Data. This was also mentioned to some extend in the companies we surveyed, that data collected through Big Data cannot be easily evaluated without the appropriate qualified personnel.

Augmented and Virtual Reality (AR/VR) have been mentioned in the literature reviewed in relation to companies with an ETO strategy. Arkouli et al. (2021), in their study of the application of Industrie 4.0 technologies to large-scale manufacturing, mention the integration of AR technologies to assist operators in real-time assembly tasks and VR as immersive visualization for engineers in workplace design. Overall, however, there is a gap in the literature providing empirical evidence for the successful use of AR application in contract manufacturers.

Additive Manufacturing is only used by three companies in our sample, mainly to produce prototypes or spare parts. Strandhagen et al. (2020) mentions that 3D printing is mainly used for manufacturing spare parts in shipbuilding, but for it to become more relevant, Additive Manufacturing needs to be further developed to solve the current quality issues. Jha (2016) adds that 3D printing is gaining importance in ship repair (due to their long-life cycle) and in logistical support (by reducing inventory costs when printing spare parts ‘on-demand). An analysis of the implementation of 3D printing in the ETO environment was described in the work of Oettmeier and Hofmann (2016) and Jha (2016). More studies should examine different use cases of 3D printing in the ETO context.

5.6 Losses due to inefficiencies in the assembly on-site

When it comes to productivity losses caused by on-site assembly or installation, qualitative Lean tools such as TQM, TPM and Six Sigma were applied by only a few of the interviewed companies, even though these tools are discussed in the scientific literature in the context of companies with an ETO strategy. Tomašević et al. (2021) found that while TPM is commonly applied in the context of Lean manufacturing, it is not discussed in the literature in the context of HMLV. Similarly, they found that TQM and Six Sigma are hardly discussed and the evidence in the research is mostly anecdotal.

Kaizen, or the Continuous Improvement Process (CIP), is one of the most cited Lean tools in this loss category to reduce inefficiencies created by on-site processes. The literature emphasizes the importance of CIP in maintaining the improvements achieved and establishing a culture of continuous improvement (Bertolini and Romagnoli 2013; Bajjou et al. 2017; Cannas et al. 2018). Bertolini and Romagnoli (2013) emphasize that any Lean project must incorporate CIP, as the results achieved are never final solutions but require unceasing improvement, which should include actions such as waste elimination, operator involvement, and Lean tools like 5S and VM. Prefabrication is mainly applied by the interviewed construction and shipbuilding companies. Further, the literature focuses on use cases mainly in construction, emphasizing the proper integration of planning and control for prefabrication in complex ETO environments (Peñaloza et al. 2016). Standardization is an important Lean tool used by the interviewees, even though only Fazinga et al. (2016) analyzed Standards for construction in a case study, finding that workers are often unaware of Lean concepts and standards because they are only moderately involved in decision-making processes. The construction and shipbuilding companies surveyed reported similar issues in establishing operational Standards, as they often employ temporary workers on-site or on the docks.

Interestingly, Benchmarking is only applied by one construction company and not mentioned in the literature in connection with ETO. It seems that the individual situation and organization of most companies with an ETO strategy does not allow a simple benchmark comparison. Gemba Walk and Daily Huddle Meeting are mainly used by construction companies. They are also mentioned in the literature in the context of construction (Hussain et al. 2020; Powell et al. 2021) to be used with VSM to establish a current value stream map or to swiftly identify areas in need of improvement. Kanban and JIT are often used in conjunction and are well discussed in the literature (Kruger 2012; Kjersem et al. 2015; Powell 2018) with regard to HMLV or ETO environments. But Adlin et al. (2020) points out that the local starting point of each company must be considered, as well as contingent factors such as the organization's learning maturity and operational maturity. Among the companies interviewed in this research, 5S and Visual Management (VM) are mainly applied in construction and shipbuilding to avoid losses due to inefficiencies in on-site activities. in the literature, VM practices are extensively discussed in construction (Tezel et al. 2016, 2017) and less so in other ETO environments (Pandian et al. 2010; Irani 2011; Cannas et al. 2018).

Surprisingly, Cloud Computing was also the only I4.0 technology directly applied by the surveyed companies on sites to minimize losses on-site. This is because the companies surveyed often still work very traditionally on-site assembly, and new technology is only slowly finding its way in. Especially in construction, where complex processes with different stakeholders under high variability make it difficult for new technologies to penetrate existing processes. This was also confirmed in the literature by Cifone and Portioli Staudacher (2022), who showed that the adoption of Lean I4.0 leads to better performance improvements in repetitive than in non-repetitive companies and that the implementation of these paradigms needs to address the intrinsic companies characteristics.

As the survey findings indicate, Lean and I4.0 practices are applied in a different way to reduce common losses in the investigated ETO companies. Standardized Work is the most commonly applied Lean tool among the sample, indicating that setting and improving standards of working procedures has stabilizing effects and forms the basis for CIP activities (Pereira et al. 2016). This seems obvious because, as a rule, processes in the project manufacturing business are variable and volatile due to fluctuating incoming orders and customization, therefore the attempt to standardize as many processes as possible (Birkie and Trucco 2016).

Horizontal and Vertical Integration are the most applied I4.0 practices among the interviewed companies, even though only limited references in the literature were found. Strandhagen et al. (2020) propose nine digital solutions and mention the importance of integration with suppliers (horizontal integration) and between higher-level IT systems and the shop floor (vertical integration) to enhance economic and social sustainability. Here, the authors point out that integration between actors in the shipbuilding supply chain is challenging but emphasize the use of Industry 4.0 technologies to facilitate supply chain integration and vertical integration of digital platforms. Similarly, Vertical Integration is frequently applied by the interviewees but only mentioned by Thun et al. (2022), who, in a study of the key enablers for digitization in ETO manufacturing, emphasize that extended collaboration between different levels of hierarchy (vertical integration) is important to build shared trust between stakeholders and make the implementation of digitalization more likely. There seems to be a lack of literature that specifically addresses the concerns of project manufacturers, particularly with practical examples.

To summarize, RQ1 Which Lean methods and I4.0 technologies and concepts are used in practice by companies with an Engineer-To-Order strategy to reduce common losses? could be illustrated based on the empirical investigation and the comparison with the analyzed literature. All Lean practices identified in the literature that try to mitigate common losses in ETO based manufacturing organizations were applied in the analyzed sample of this research. However, there are several gaps in the literature. Lean tools to reduce losses due to customer and engineering inefficiencies, such as IPD, Detailed Briefing, Concurrent Engineering, Value Based Management, Virtual Design Construction, Target Value Design, Design Structure Matrix, and Design Workshops have all been encountered in practice but not in the scientific works. This gap in the project manufacturing environment needs to be addressed with further empirical investigation. In contrast, the Lean tools for reducing losses in production and assembly on-site areas were all found in practice and literature. This confirms the often-one-sided focus of Lean on the direct production processes.

Considering the application of I4.0 technologies, all previously in the literature identified technologies were also found to be used in practices in the sample. However, different gaps were also found here. No technologies to reduce customer-related losses were used by the cases, as well as only Cloud Computing was used to reduce losses during assembly on-site even though more technologies were found in the literature. This implies that ETO companies need more support in the implementation of I4.0 technologies backed by empirical studies. Further, there are differences in the degree and extent to which Lean and Industry 4.0 practices have been applied in the surveyed companies, ranging from full implementation to only partial adoption.

Regarding RQ2 Are there certain practices from Lean and Industry 4.0 that are applied in practice in companies with an ETO strategy that are not discussed in the literature and vice versa? can be answered with yes. Lean tools like Integrated Project Delivery, Detailed Briefing, as well as Concurrent Engineering were encountered in the case companies interviewed, but not in research in terms of reducing customer-caused losses. Similarly, Value Based Management, Virtual Design Construction, Target Value Design, Design Structure Matrix, Design Workshops were not mentioned in the works with respect to an ETO context for mitigating losses caused by inefficiencies by the engineering department but were met in practice. This is also evident for the Lean methods Work Structuring and Scheduling and Conference Management, which were applied by the analyzed case companies but not discussed in the literature for reducing losses due to inefficiencies in the project department. Likewise, the Lean tools First Run Study and Benchmarking were applied in practice but not mentioned in the analyzed literature for reducing losses caused by on-site assemblies. Similarly, Industry 4.0 technologies such as Cybersecurity, Product and Process Simulation, and MIS were all encountered in practice but not in the literature.

5.7 Other observations

Comparing the use of Lean tools and Industry 4.0 technologies in the ETO companies surveyed, Lean tools and methods are used much more frequently in practice than Industry 4.0 technologies. One reason for this is that Lean and its applications in many different industries and production environments have already been discussed at length in the literature. The literature goes back to the 1990s and even further with the Toyota Production System (Liker 2004). While Industry 4.0 has only been properly mentioned in the literature since the early 2010s. However, the origins of some technologies from the fourth industrial revolution have been studied in the literature much earlier (Büchi et al. 2020). Another reason is the focus of the application of Industry 4.0 technologies on repetitive forms of production and less on the non-repetitive types, such as ETO and HMLV environments. This is evident from the literature analyzed, which is also reflected in the significantly fewer sources for Industry 4.0 in contract manufacturing. The related literature is also rather anecdotal and characterized by less successful implemented practical examples. The interviews also highlighted that the introduction of Industry 4.0 technologies in an ETO context still faces many barriers, such as a lack of skilled workers or the technological immaturity of some technologies. At this point, further research is needed on how to mitigate these implementation barriers and highlight successful Industry 4.0 implementations in project-based manufacturing environments.

It is also noticeable that many techniques and methods from both Lean and Industry 4.0 are already being used in practice by the case companies interviewed but have not yet been researched at all or are little discussed in the literature, such as Benchmarking or Cloud Computing. However, it must be emphasized that the degree of application varies from case company to case company. Some firms consistently apply a Lean or Industry 4.0 technology in their organization, while others are still in the testing phase or have not even considered a particular method or technology. For example, case companies B and E mentions that most Industry 4.0 technologies are only being tested in various projects, for example drilling robots or sensors to track material and components. “A lack of experts familiar with Industry 4.0 transformation and a lack of training and qualification of the workforce regarding Industry 4.0 as well as a general lack of trust in the construction industry” as cited as the major obstacles for more Industry 4.0 application by both case companies. Interviewee from case company I point out that “the existing IT infrastructure is not able to implement more digital technologies”. This could explain, among other things, why so few Industry 4.0 technologies are currently being used in an ETO context, especially in the construction.

Another way to mitigate or remove barriers to the adoption of Industry 4.0 technologies is to collaborate with start-ups. In our study, several surveyed companies indicated that they collaborate with startups to promote the adoption of Industry 4.0 technologies. For example, case company C is working with a startup that has developed a photogrammetry software to use a camera to perform a target-actual comparison between a BIM model and the real building. Another startup deploys and tests sensors for material tracking. However, these are isolated cases and the successful application in daily operations of these case companies remains to be seen.

In our study, we found additional techniques and technologies in the companies interviewed that were not found in the literature examined. This includes Takt Planning, a widely used Lean tool in the construction industry. Takt Planning is often used individually or in connection with LPS to achieve scheduling and productivity improvement by aligning available network time with actual customer demand in a given time period. Another emerging technology that was used by the companies surveyed but not mentioned in the literature is Bluetooth 5.0. For example, one shipbuilder studied uses Bluetooth 5.0 as a kind of extension of the Lean tool LBMS. With Bluetooth 5.0, the operator knows exactly where he is on the ship. Errors can be reported back quickly and precisely, especially when there are many process steps at one point or task with many different trades. It would be interesting to know if Bluetooth 5.0 would also be successful in other use cases and with other Lean tools in the ETO context.

Another technique not mentioned in literature we analyzed is the use of time study methods or ‘Work sampling’ such as Multi-Moment-Analysis (MMA), where the frequency and time requirements of processes in work systems are captured and analyzed in a multi-moment study. Case Study Company B uses such work sample procedures to optimize and standardize repetitive activities. Further, this company also uses a shopfloor management method (SFM) based on concepts such as Gemba walk and Daily Huddle meetings to identify and solve problems where they occur and to prevent bottom-up initiatives from failing short. Errors are either resolved on site or escalated upward. SFM is considered as a prerequisite for implementing Lean systems since because it both standardizes processes and establishes the necessary organizational structure at shop floor level (Gaspar and Leal 2020).

Another method applied by one of the interviewed case companies is Business Process Modeling notation (BPMN), a visual tool for analyzing and designing business processes at a different level of abstraction with the goal of improving them. In doing so, BPMN facilitates communication between different company personnel, such as business analysis, IT developers, or managers, to support decision making related to cost analysis, scenario analysis, and simulation (Decker et al. 2010). A possible connection of Lean and Industry 4.0 with BPMN to reduce losses would be worth investigating.

All respondents in contract manufacturing are initially concerned with Industry 4.0 and digitization, although the construction industry is less affected and shipbuilding more, as it is stationary compared to construction (dock or shipyard). The introduction of Industry 4.0 is generally difficult for quantities of one or to produce one-of-a-kind (OKP) items, as a high degree of individualization (e.g., yacht building) and a lot of manual labor leave little room for meaningful application Industry 4.0. High development costs are also an obstacle mentioned by the companies interviewed. Technological progress can make Industry 4.0 technologies significantly cheaper and easier to use.

The degree of digitization depends heavily on the ETO industry. As interviewee Q emphasis, shipbuilding, has always worked in a complete data model, but the difficulty lies in the variety of different trades (e.g., steel construction and interior finishing) which work differently and accordingly with different systems. In general, a standardization or platform strategy is being pursued in the ETO area. Despite the high degree of customization of the products, there are advantages in particular in prefabrication (Schulze and Dallasega 2021).

Some of the main reasons for the low penetration of Industry 4.0 technology in the ETO area are the financial investment required, the technical immaturity of various Industry 4.0 technologies and the lack of best practices or a corresponding guide to help firms implement them.

5.8 Implications for research

This study contributes to the literature by providing an empirical validation of the practical application of Lean tools and Industry 4.0 technologies in different companies with an ETO manufacturing strategy. This paper also took a holistic view of the implementation of Lean and Industry 4.0 by studying both the academic literature and the practical implementation of these tools and technologies in various typical ETO settings, such as construction, shipbuilding, and machine and plant manufacturing. There is a need for more empirical research in the context of ETO manufacturing, as there is a clear lack of best practices and guidelines for specific Lean tools and Industrie 4.0 technologies in the literature. Research needs to investigate the extent to which these practices can be successfully applied in companies with an ETO strategy and the extent to which any implementation barriers that occur can be overcome. Best practice solutions and guidelines should be identified to what extent Lean tools and industry 4.0 technologies are used in various ETO scenarios. This is in line with Adlin et al. (2020), who emphasize the need to adapt Lean implementation efforts to local conditions and align with other practices and strategies in improve productivity.

Our framework can be used by companies in ETO sectors that do not have extensive R&D departments as a basis for understanding how losses can be mitigated through the application of Lean and I.40 practices. This is especially relevant because project manufacturers often rely on IT companies or similar technology suppliers to provide I4.0 technologies and typically do not identify and select themselves which tools and technologies they should use to reduce common losses.

5.9 Implications for practice

There are some key insights for practitioners in companies with an ETO strategy regarding actions to avoid losses (Table 4). First, managers should consider their distinct ETO characteristics when considering the introduction of Lean or Industrie 4.0 technologies, as organizations with an ETO strategy need management approaches that are compatible with their organizations. More importantly, the adoption of Lean and I4.0 practices should be an incremental process and results require time (Adlin et al. 2020). Further, reducing losses in the development department has been little discussed in the literature analyzed, and the companies studied also had difficulty implementing it. In this respect, practitioners should consider that there is a lack of corresponding guidelines here. The Lean tool VSM was nevertheless used with some adaptations in different HMLV environments to detect wastes and losses. Managers should however consider their individual situation and may need to develop their own VSM adoption to suit their needs. Practitioners for whom quality assurance is an important priority in their operations, especially on-site assembly, will have difficulty finding appropriate instructions of Lean quality tools adaption to ETO environments in the literature. Practitioners should find their own approach. Further, managers should be aware of the amount of training required to introduce Lean and I4.0 practices and to establish standards or standardized work procedures, especially with temporary workers in construction and shipbuilding settings. Practitioners should also be aware that it is hard to find adequate benchmarking studies or best practices for the ETO environment that can easily be applied in their own setting. Contingency factory such as learning ability, maturity level of Lean and I4.0 practices should be considered. Several Lean tools and Industry 4.0 technologies have been sufficiently researched in the literature in terms of application in the ETO environment, while others, on the other hand, do not appear in the literature. Accordingly, managers should leverage existing published research, but anticipate potential setbacks in implementing these Lean tools and Industry 4.0 technologies in the absence of successful best practices or guidelines. However, some I4.0 technologies, like IoT-enabled devices like sensors and Cloud Computing solutions are already widely applied in the analyzed sample and can serve as useful examples for the company's own implementation. For both technologies, data security is an important aspect to consider as well as finding the appropriate qualified personnel able to analyze the collected data. Further, our study has shown that Lean was more employed than I4.0 in the cases surveyed which is also reflected in the literature analyzed. Managers seeking guidance from the published literature should consider these limitations.

Table 4 Implications for practitioners in companies with an ETO strategy
Full size table

And last, managers should consider that there are barriers to the application of Lean methods and Industry 4.0 technologies in companies with an ETO strategy (Orzes et al. 2019; Schulze and Dallasega 2021). Therefore, managers should also observe and identify barriers in their own organizations, both in terms of Lean practices and Industry 4.0 technologies.

5.10 Research limitations

Regarding the limitations of this investigation, it must be mentioned that the empirical study is limited to 16 companies with an ETO production strategy. All participants' responses relate to their individual company and situation, and there may be different perspectives within the broader ETO sector. However, companies from three main ETO sectors were considered, reflecting the main characteristics of this sector: i) machine and plant manufacturers, ii) construction and iii) shipbuilding. Next, due to the pandemic, not all companies could be visited on site and not all interviews could be conducted in person. Around half of the interviews were held online. As a result, it was not possible to conduct an in-depth visit to the company to better understand the context and some organizational issues. However, the semi-structured interviews consisted of three steps; first, the questionnaire was sent prior to the interview to allow the respondent to reflect on, understand, and complete the various questions; second the semi-structured interview was conducted based on the completed questionnaire; and third, a summary of the discussion and comments on the questionnaire was sent back to the interviewee for validation. Furthermore, the locations of the respondents were mainly limited to the European continent. Specifically, we considered companies from South Europe (e.g., Italy), Central Europe (e.g., Germany) and Northern Europe (e.g., Norway) to obtain an overall picture of this continent.

Considering the literature review, we mainly used Scopus as our scientific reference database. However, Scopus can be considered one of the largest scientific databases as it covers a considerably larger number of published articles than its counterparts (Guz and Rushchitsky 2009; Chadegani et al. 2013; Aghimien et al. 2019). The use of a single accessible database also helped to reduce the problem of duplicates of extracted articles. Moreover, the literature review (Sect. 2) considered journal articles and conference proceedings. However, books, book chapters, dissertations, and white papers, that might be considered for future research were not included. Journal papers were considered because of their peer reviewed content and conference papers because of the potential for new findings.

5.11 Future research directions

Some of other opportunities for future research have also been identified in this research. For one, the emergence of Lean tools and methods in additional sectors of companies with an ETO strategy could be explored. For example, how do contract manufacturers of very large parts (such as oil rigs) or of niche products (such as race cars) cope with the implementation of Lean principles and methods in their organizations? Next, our research focused on Lean methods and Industry4.0 tools and concepts. Future research could examine other methods besides Lean, to improve efficiency and reduce waste, such as Agile Manufacturing, Mass Customization, Quick-Response Manufacturing (QRM) and Project Management methods. Further investigation should also use additional empirical case studies to explore how technologies and concepts from the fourth industrial revolution (Industry 4.0) could mitigate Lean implementation barriers. For example, Miqueo et al. (2020) mention that the digitization of Lean tools, such as Value Stream Mapping with Simulation, could facilitate application, or that Industry 4.0 technologies such as Virtual and Augmented Reality can be used to improve the training environment to make it easier for employees to learn Lean. Since certain Lean tools and methods were encountered in practice rather than theory in the study, there is an opportunity to research and publish more about them. For example, Poka-Yoke, IPD, and LBMS have not frequently been described for use in an ETO context. Furthermore, the barriers to implement Industry 4.0 technologies and concepts specifically in organizations with an ETO manufacturing strategy should be researched and empirically validated. Several publications have already explored barriers to adopting Industry 4.0 technologies in repetitive manufacturing settings, but not particularly in project-based non-repetitive situations (Orzes et al. 2019).

Future research could also narrow the scope of the research by focusing on one single sector like machine building but with a larger sample size to attain more detailed insights into how losses are reduced by an integrated Lean and I4.0 approach.

6 Conclusion

Based on a literature review as well as survey questionnaires and semi-structured interviews with sixteen companies with an ETO order fulfillment strategy, this paper analyzed and compared the application of Lean tools and methods as well as Industry 4.0 technologies in practice and in the literature that are able to reduce common losses in these organizations.

The research was guided by our research questions: (i) which Lean and Industry 4.0 practices are applied by companies with an ETO strategy in practice and (ii) whether Lean and Industry 4.0 methods applied under real working conditions are also discussed in the scientific papers or not. In line with the research questions raised, the findings reveal that the analyzed companies from the construction, shipbuilding, and machine and plant manufacturing sectors apply Lean tools and Industry 4.0 technologies to varying degrees to reduce losses. There are several Lean methods and Industry 4.0 technologies that are applied in practice, but not in the analyzed literature. Further, the literature lacks theoretical and practical research regarding on the application of industry 4.0 practices in the ETO environment, as the articles mostly lack empirical evidence. The findings also suggest that the surveyed companies apply other productivity improvement techniques, such as work sampling or is Business Process Modeling notation (BPMN), as well as Industry 4.0 technologies not mentioned in the literature, such as Bluetooth 5.0. The integration of Lean and Industry 4.0 is considered in the literature but has not been extensively researched and empirical evidence in the ETO context is lacking. Lastly, the results also indicate that the companies interviewed face various barriers to implementing Lean practices or Industry 4.0 technologies in their organizations.,

The contribution of this paper is multifaceted. From a theoretical perspective, it adds to the widely incomplete and fragmented field in the literature examining the implementation of Lean and Industry 4.0 in practice in companies with an engineer-to-order manufacturing strategy. Various gaps in the literature regarding empirical evidence of the application of Lean and Industry 4.0 practices could be identified. Moreover, we hope to encourage further evidence-based research in this area to provide companies with an ETO manufacturing strategy perspective of reducing common losses. Practitioners can benefit from a better understanding of applied Lean and Industry 4.0 practices in common engineer-to-order industries for their own efforts to reduce productivity losses. Thus, managers should also be aware of losses not only within their own organization, but also within their supply chains.

The explanatory power of this study is somewhat limited due to the sample size and the focus on shipbuilding, construction, and machine and plant manufacturers in the ETO environment. Further, not all interviews could be conducted in person on site. Therefore, although exploratory studies are important to deepen knowledge in new research areas, the findings cannot be easily generalized but provide a good starting point for further investigations.

The explanatory power of this study is somewhat limited due to the sample size and the focus on shipbuilding, construction, and machine and plant manufacturers in the ETO environment. Further, not all interviews could be conducted in person on site. Therefore, although exploratory studies are important to deepen knowledge in new research areas, the findings cannot be easily generalized but provide a good starting point for further investigations.

Future research should provide more insights into practical application of Lean and Industry 4.0 practices to mitigate losses in organizations with an ETO strategy and provide best practices and guidelines, especially for those tools and methods that are underrepresented in the literature analyzed. Of particular interest would be research that further explores the proposed potential of Industrie 4.0 technologies to reduce barriers to Lean implementation in companies with an ETO strategy. Furthermore, case studies from other areas of the ETO environment would be of value to improve generalizability.