1 Introduction

Production in global production networks (GPN) is playing an increasingly important role in the context of intensifying worldwide competition and accelerated globalization of sales and procurement markets. This has resulted in GPN characterized by diverse supply and service interdependencies between individual internal company locations and locations of external players such as suppliers and customers [1].

To remain competitive and to be able to respond to individual customer requirements, companies must constantly develop their products and services further [2]. This means that companies are forced to start the production of new products at invariably shorter intervals and to make corresponding adjustments in their production network [3]. Due to diverging target systems integrating e.g. time, costs, quality, complexity, and uncertainty, the production ramp-up represents a critical phase in the life cycle of a product [2]. Accordingly, the ability to introduce products within the given time, cost, and quality framework becomes a decisive competitive advantage [4]. Practitioners often fail certain targets during production ramp-ups due to the complexity of the task [5].

The duration influences the success of the ramp-up since earlier market entry can lead to high prices compared to competitors. In addition to the profits lost due to ramp-up delays, the direct ramp-up costs are also relevant for a successful ramp-up [6]. Inefficiencies in the ramp-up process should therefore be avoided despite its complexity [3]. On average, direct ramp-up costs account for around 20% of the investments in buildings and equipment made by enterprises [7]. They are incurred for the training of newly hired employees, for building up additional safety stocks to maintain delivery readiness, or for new operating equipment [5]. The reasons for the large differences in production ramp-up costs, times, and qualities between companies in different industries are mainly due to the complexity and management of the ramp-up process so that companies with extensive experience in ramping-up can achieve significant benefits [6].

If a production ramp-up takes place in an enterprise with more than one production plant, further challenges arise due to the dynamics as a result of the mutual influences between the production plants and the supplier relationships [8]. This results in new global influencing factors for the production ramp-up in networks. Furthermore, different production plants in GPN have different cultural, process or product influences which need to be considered when managing production ramp-ups [5]. Currently, there is no methodology for efficiently managing the production ramp-up parallel at different production plants that integrates analysis of the above-mentioned aspects of the target system, influencing factors, and the planning and control of production ramp-ups in GPN. Therefore, this paper introduces a practice-oriented methodology for the efficient management of production ramp-ups in GPN.

2 Fundamentals

Products are provided by GPN which uses specific resources and competencies of distributed production plants [1]. The structure of a GPN is defined by open-ended edges and nodes. Nodes represent different production sites, related suppliers and customers. The edges are connections between the sites and can imply material, information, or financial flows [9]. The environment of GPN is typically dynamic and complex. The above-mentioned perspective distinguishes GPN from common supply chains which focus on the step-by-step provision of industrial goods [1].

A specific stage in the product life cycle of each product is the unique ramp-up of production. It is characterized as the stage between product development and series production. In comparison to the following series production, the production ramp-up has characteristic features that must be considered during management. Due to the degree of novelty of product and process as well as the lack of experience, especially in SMEs, more errors occur in the production ramp-up than in stable series production [10]. For this reason, it may be necessary to interrupt production frequently to rectify the problems that occur. Hence, there are greater uncertainties and thus more risks during production ramp-up. The production ramp-up can be divided into three phases (see Fig. 1) [11].

Fig. 1
figure 1

Phases in industrial production

Before the actual start of production (SOP), the pre-series and pilot series take place. In the pre-series, the initial production of larger quantities is an attempt to bring production closer to series conditions [11]. The aim is to obtain information on the optimal design of the production process itself, as well as on the tools and machines used [12]. In the pilot series, production is as close as possible to series production conditions for the first time. This means that only series tools are used in a pilot series and that the procurement of all materials and parts also corresponds to the later series conditions. The pilot production aims to check whether the planned production process can continue to be carried out without problems under series production conditions and ultimately produce a product of required quality. Once the trial runs of the series production in pre-series and pilot series have been completed and the identified potential for improvement has been implemented, the actual production for the market begins. The phase after SOP, which aims at reaching the planned production quantity is called production run-up. During the run-up, the company needs to identify and eliminate possible problems and malfunctions in production at an early stage to achieve a stable production process with the previously defined quality level in the shortest possible time [11].

Production ramp-ups in GPN are influenced by external factors and their uncertain future developments. They are influenced, for example, by cultural or political factors that differ between different production sites in a GPN [1]. One methodology to support decisions in an uncertain environment is the scenario technique. The scenario technique is based on the principles of interlinked thinking and multiple futures. The principle of interlinked thinking focuses on the analysis of the interlinkage of external influencing factors. The principle of multiple futures develops visions of the future based on the development paths of these influencing factors [13].

Production ramp-ups can be categorized as projects due to the defined start and endpoint, the measurement of time, cost, and quality, and their measure: the degree of fulfilment, or the efficiency [2]. A project is defined as an “initiative that is characterized by the uniqueness of its conditions as a whole”. For ramp-ups, necessary conditions are external influencing factors, but also restrictions on personnel and cost [3]. Therefore, ramp-up management can be described as project management which is defined as “all leadership tasks, organization, techniques, and means that are necessary for the initiation, definition, planning, steering and completion of projects” [4].

During production ramp-ups, several tasks in the field of planning and managing are necessary. These tasks are combined with to term “management of production ramp-ups” [14]. For the successful fulfilment of the tasks, processes are defined where disruptions might occur. Disruptions are deviations from the target state of a system or a project [15]. In disruption management, one differentiates predictive and reactive disruption management. While predictive disruption management aims to minimize the occurrence of disturbances in advance, reactive disruption management takes place when a disruption already occurred. [5]

3 Literature review

In the following section, existing approaches concerning ramp-up management in GPN are presented.

Surbier et al. give an overview of the international state of research on the topic of the production ramp-up. They claim that the approaches in the literature are mostly only research studies or field studies, as ramp-up management is still a young field of research. Few studies contain quantitative models that describe the system behaviour utilizing key performance indicators [6]. However, different authors have identified key performance indicators related to the ramp-up [8, 16, 17]. The further work of Surbier et al. deals with the exchange of information between the stakeholders of the ramp-up process. Utilizing a model for analysing the interfaces between the stakeholders: “research and development”, “production”, “purchasing and procurement”, “quality” and “factory management”, during the ramp-up process the information flows can be examined for weak points and possible improvements [18]. Di Benedetto looks at strategic, tactical, and information-related activities that influence the success of a new product launch. His survey of individual activities of past product launches in companies concludes that successful product launches have been achieved by cross-functional teams from marketing, production, and logistics [19]. Quick and Renner present aims and corresponding key performance indicators for the ramp-up in supply chains, whereby supply chain aims are assigned to the ramp-up goals according to the SCOR model and are thus implicitly considered by the ramp-up goals [14]. Renner conceives a guideline for the development of a ramp-up-specific “Performance Management System”, considers the influencing factors of the production ramp-up and categorizes them in complexity and novelty of products and processes as well as dynamic aspects. Influencing factors in global production networks are not explicitly addressed so that their possible target effects are not considered. For example, it remains open which product- and production-related factors are of particular relevance according to the location factors at a particular production site. Further, the research does not focus on the extent to which the complexity and novelty of products and processes exist at globally distributed locations due to corresponding site-specific production adjustments, relevant stakeholders, and different location roles or strategies [20]. Ulrich aims for the goal of developing a methodical procedure for the targeted handling of disturbances in the production ramp-up. For the targeted use of measures, he designs a comprehensive characterization of disturbances related to the categories “disturbance objects”, “types”, “locations”, and “causes”. Their characteristics are further refined and described. However, they are not considered in the course of the model development. It is a toolbox that contains a multitude of methods for dealing with disturbances. Within this toolbox, the individual methods are assigned to the different phases of disturbance management. The author describes the individual methods in detail. However, it remains unclear how these methods have to be applied and to what extent they are helpful in practice. A validation by experts and an implementation in a software demonstrator are missing [21].

The aforementioned approaches show that the management of production ramp-ups is a relevant field in the context of global production research. In practice, there are many company-specific procedures for managing production ramp-ups which often miss a methodological support. Therefore, an integrated consideration of the target system, influencing factors, and the management of production ramp-ups with a focus on SMEs lacks in research and practice.

4 Methodology for an efficient production ramp-up in GPN of SME

The following chapter describes a practice-oriented methodology for an efficient production ramp-up in GPN of SME. The focus of the approach is the straightforward and integrated consideration of aims, influencing factors, and the management of production ramp-ups. The methodology is divided into three steps which are inspired by classical project management [22]: First, the analysis of the target system and influencing factors of the considered ramp-up; second, the in-detail planning of relevant tasks during the ramp-up integrating the setting of milestones and a project plan; third, the integration of a disturbance management model to handle disruptions in the ramp-up ensuring a successful realization of the ramp-up project (see Fig. 2).

Fig. 2
figure 2

Overview of the methodology for efficient production ramp-ups in GPN

4.1 Analysis of target system and influencing factors

The aim of the first phase of the presented methodology is the analysis of the target system and relevant influencing factors of production ramp-ups in GPN.

To efficiently design production ramp-ups, both the knowledge of all methodical and content-related targets of the ramp-up and suitable key performance indicators for monitoring, are necessary. Based on an extensive literature review and expert workshops, seven six targets were identified. Despite the three classical targets cost, quality, and time, flexibility, risk and sustainability were also identified. For each of these targets, suitable key performance indicators were identified. In total, 45 key performance indicators were developed and can be used for measuring the efficiency of ramp-ups. The targets can be individually hierarchized with the help of an Analytical Hierarchy Process (AHP). Hence, a company-specific target system is generated.

Second, classical influencing factors of global production were identified based on a comprehensive literature review. These are generally divided into the subject areas “network factors (displayed in Fig. 3)”, “location factors”, “product and production-relevant process factors”, “production adjustments”, “plant roles and stakeholders” in general. The influencing factors are relevant for the network, plant, process, and product level. Each factor has different influences on the production ramp-up depending on the ramp-up itself. In total, 33 key influencing factors were identified. These factors are displayed in the following excerpt of a morphological box (see Fig. 3). They help SME by structuring their production ramp-up and enable them to gain a deeper insight into relevant factors. The full list of relevant key influencing factors can be found in the Appendix 1.

Fig. 3
figure 3

Excerpt of the morphological box of key influencing factors

Thus, companies can carry out a self-assessment to estimate how complex the considered production ramp-up is. This is called the influence profile of the production ramp-up.

These key influencing factors are the basis for the scenario analysis based on Gausemeier and Fink [13]. In the first step, the scenario preparation, the objective of the production ramp-up has to be determined. It is determined by the target system. In the second step, the design field, relevant influencing factors are identified. The influence profile is used for this step as only influencing factors with a high complexity are considered. During the third step, future projections of the influencing factors are generated and combined into consistent scenarios [13].

4.2 Ramp-up planning

The second phase of the methodology for efficient production ramp-ups in GPN aims to create a detailed plan for the ramp-up project and to connect it with the target system and the key influencing factors.

Production ramp-ups consist of a large number of complex and interdependent processes. A decisive challenge companies are facing during production ramp-ups is the planning, organization, and control of these processes. Despite their high complexity, ramp-up projects have common features that enable the development and use of ramp-up reference processes. A ramp-up reference process is a transparent description of the chronological and logical sequence of processes, sub-processes, and milestones as well as the responsible functional areas of a production ramp-up. The ramp-up reference process aims to map the processes in a holistic and generally valid way. It therefore represents a modularly adaptable and reusable template for a large number of ramp-ups to derive specific ramp-up processes.

At the top level of the ramp-up reference process, the most important functional areas of a manufacturing company are human resources, research & development, factory planning, production, logistics, procurement and purchasing as well as marketing & sales. A detailed explanation of the ramp-up reference process can be found in the Appendix 2.

A total of 28 processes is assigned to these seven functional areas on the second level. They cover the entire product development process and thus ensure a holistic view of the production ramp-up. The respective processes are displayed clearly in the form of arrows in chronological order. However, to be able to exactly define the start and end time of a process, the start date and the process duration must be defined for this process within the framework of a specific ramp-up project. If possible, the immediate predecessor process of the process must also be determined. For example, the immediate predecessor of the recruitment process is “headcount planning”. This means that the recruitment process can only be started after the planning of personnel requirements has been completed. It is important to also determine the predecessor process, since this may affect the start date of the process. The longest process sequence, in which each process has an immediate predecessor and there are no breaks between processes, is called the critical path in project management. The delay of a ramp-up process in a critical path results in the postponement of the entire production ramp-up. If the immediate predecessors of the different processes and thus also the critical path is known, such a delay of the production start can be detected early and counteracted.

On a third level of the ramp-up reference process, further detailing is possible by assigning additional sub-processes and interfaces to external actors to the individual processes. For reasons of clarity, a maximum of three sub-processes and a possible interface to external actors are assigned to each process. Therefore, the identified sub-processes only represent a selection of all possible sub-processes of a ramp-up. To illustrate the relationships just described, Fig. 4 shows the “Personnel Requirements Planning” process with the three sub-processes “Diagnostic Phase”, “Forecast Phase”, “Action Phase”. The diagnostic phase is used to determine the current headcount. In the subsequent forecast phase, the future headcount is forecasted. The actions of the personnel acquisition are then determined in the action phase. All relevant tasks are displayed in the description of the sub-processes.

Fig. 4
figure 4

Exemplary process “Personnel Requirements Planning” with sub-processes

Milestones are introduced as part of the ramp-up process planning to be able to evaluate the progress of the project and the synchronous progress of the parties involved at a later stage and to thus be able to make decisions on how to proceed.

The key influencing indicators can now be mapped individually to the sub-processes of the ramp-up reference process. With the help of the relevance profile of the overall ramp-up, each process is checked regarding an influence. The ramp-up manager gets an easy overview of each relevant external factor for the different ramp-up processes which helps steer the ramp-up efficiently.

The processes are integrated into a project management chart (see Sect. 5, Fig. 6). The chart is completely modular for the user and can be individualized. Further, the identified target system is implemented in the chart. For optimization purposes, the shortest-path method is integrated as the main target regarding time [23, 24]. For SME, time is the most decisive factor of production ramp-ups due to resource commitment [3]. Other targets can also be displayed in the project management chart for performance screening purposes.

4.3 Disruption ramp-up management

The last phase of the practice-oriented methodology for efficient production ramp-ups in GPN of SME aims at integrating a disruption management approach to the planning of ramp-ups. With disruption management, the control of ongoing ramp-ups is enabled.

The categorization of disruptions is based on the 5M of the Ishikawa diagram [25]. The Ishikawa diagram is widely used and is therefore suitable for usage in SMEs. The 5M are specified for the production ramp-up as man, machine, material, process (method), environment (measurement). All possible root-causes of disruptions can be displayed in the Ishikawa diagram. A detailed description of possible disruptions is made for each root-cause. 58 possible disruptions are identified by literature review and complemented by expert workshops. They are categorized and can be found in the Appendix 3.

The production ramp-up at a new production plant is a challenge, especially for SMEs. They often lack experience and knowledge they can rely on [21]. If disruptions occur during the production ramp-up, these must be dealt with as quickly as possible by action measures to correct the deviations from the plan and to not jeopardize the successful implementation of the ramp-up. The derivation of suitable measures is a decision-making process which, against the background of the lack of experience, takes too long depending on the disruptive situations in SME [11]. To accelerate this decision-making process, the methodology, based on the designed categorization system, includes more than 200 reactive and action measures. The reactive and action or preventive measures can be found in the Appendix 4.

To clarify disruptions and measure, an example is given in the following: a disruption occurs during a production ramp-up due to poor quality of the delivered components. The cause for this lies at the supplier site. According to the categorization system, "quality" is the decisive factor. For this disturbance, the following reactive action measures are defined and can be selected by the company: supplier support by experts of the company, definition of a standardized test procedure for quality control, carrying out initial audits, let suppliers develop measures to eliminate the weaknesses (e.g. increase process reliability, improve quality control), follow-up review or audit to check the implementation of measures. For predictive purposes, several action measures are defined to minimize the happening of disturbances during production ramp-up.

All modules of the methodology are implemented in a software demonstrator for SME based on Microsoft Excel. With the help of the demonstrator, the SME can take advantage of the knowledge and the processes of the methodology. Hence, an efficient production ramp-up for SMEs is prepared.

For demonstration purposes, the KPI “Overall Equipment Effectiveness” is at the center of analysis in the displayed case coming from the target system. Relevant milestones are defined, KPIs are updated and mapped, influencing factors are tracked and disturbances are integrated (see Fig. 5).

Fig. 5
figure 5

Software demonstrator for efficient production ramp-ups in GPN

5 Application to industrial use case

The methodology for efficient production ramp-ups in GPN has exemplary been applied to a company in the automotive supplier industry. The production program of the company includes different engine management systems. The GPN consists of three production sites located in Europe, Asia, and Central America. The network strategy can be described as market-oriented. Each product is manufactured at only one production site. Therefore, there is no internal movement of parts in the GPN and no fragmentation of value creation. For the production ramp-up, a product for middle-class engine management is focused. It is manufactured in the production plant in Central America. The production plant in Central America can be categorized as a lead plant.

In the course of phase one, the target system was hierarchized. For the enterprise, the most important target when launching the product is to meet the specified product quality. Deviations in quality cannot be tolerated because customers do not accept them. For tracking, the enterprise used the following KPI:

$${Fulfillment \,of \,internal \,quality\, requirements}=\frac{Number \,of\, internal \,good \,parts}{Total \,number\, of\, manufactured\, parts}\times 100\%$$
(1)

The requirement of product quality is closely followed by the time requirement. The company has made precise framework agreements with the customers as to which product quantities are to be delivered and at what times. Since the customers’ production systems are based on just-in-time principles, the company risks high contractual penalties and consequently high financial losses if the delivery is too late due to a slow ramp-up. For internal tracking, the enterprise used the following KPI:

$${Ramp\, up\, time}={Total\, time\, from\, project\, start\, to\, current\, status}$$
(2)

Additionally, the third important requirement is efficient supplier management. The reason for this is that the availability of parts from a supplier is one of the biggest challenges and one of the main reasons for delays in the start of production of engine management products. Precisely, those delays have to be avoided due to the strict time requirements of the customers. For the tracking, the enterprise used the following KPI:

$${Outgoing\, on \,time \,rate}=\frac{Number\, of \,on\, time \,deliveries\, of\, products}{Total \,number \,of \,deliveries}\times 100\%$$
(3)

The qualification level of the employees in Central America was defined as most important influencing factor. As the new product was very complex in structure and production processes, there was a need for higher qualified employees. The first line construction and the pre-acceptance of the line took place in Central America. During this pre-acceptance, experts from the headquarters came to the location in Central America to inspect the machines and to test the process capability. During the pre-acceptance, the qualification of the later factory functions and line workers also took place as a result of the influencing factors of the ramp-up (see Sect. 4). During the first pre-acceptance, many process errors still occurred and the required quality and cycle time were generally not yet achieved at the individual machines and production stations. These problems, as well as the visible process improvements and bug fixes, enabled workers to develop a good understanding of the process at an early stage. Through this understanding of the processes, the workers can later pay closer attention to possible sources of error that they have already observed during the creation and rectification and avoid them. Due to this early qualification of the workers during commissioning and process analysis, the later error rate in the ramp-up and serial production decreases. This results in a higher quality level. A scenario analysis was not conducted by the enterprise due to time limitations.

In the second phase, the production ramp-up was planned in detail. Due to the knowledge of the employee qualification, the time of the respective process was estimated precisely. An excerpt of the production ramp-up process model is displayed in Fig. 6. An in-detail view of the specific processes is not possible due to confidentiality reasons.

Fig. 6
figure 6

Excerpt of the production ramp-up process model from the SME

In the last phase, the ramp-up disturbance model was used to control the production ramp-up in Central America. As displayed in the disturbance management chart in Fig. 7, one can see a transparent overview of the actual number of not solved (open) disturbances and the total number of disturbances. The chart helps the ramp-up manager to track the pain points of the ramp-up project.

Fig. 7
figure 7

Course of disturbances of the exemplary ramp-up

One exemplary disturbance was the failure of a supplier due to financial reasons. The developed model recommended not to rely on single sourcing which was implemented by the SME before the ramp-up based on the disturbance catalogue (see Appendices 3 and 4) as a preventive method. This led to the efficient handling of the disturbance. Obtaining more than one supplier primarily results in greater independence from any delivery difficulties and greater flexibility in the event of fluctuating or increasing order quantities. Also, independence from individual suppliers creates a better negotiating position due to competitive pressure among suppliers. Above all, a high level of delivery security is crucial for an efficient and secure implementation of the production ramp-up. Since delivery problems can also arise from suppliers, especially in the early phases of the ramp-up, single sourcing should be avoided as far as possible in favor of greater flexibility.

With the help of the disturbance management model and the integrated charts, the ramp-up was 16.9% ahead of the calculated time which leads to an early market entry of the engine management product and it was based on the high-quality database for disruption management and the solid planning process. Further, the quality and the supplier base were solid and led to an efficient production ramp-up regarding the overall target system.

6 Conclusion

This paper presents a practice-oriented methodology for efficient production ramp-ups in GPN of SMEs. The methodology is divided into three phases: analysis of the target system and influencing factors, ramp-up planning, and ramp-up disturbance management. The novelty of the methodology lies in the integrated consideration of target systems, internal and external factors, and operative ramp-up management. The method was successfully applied to a production ramp-up of engine management systems at a production site in Central America. In the use case, the target system and the in-depth analysis of the influencing factors helped to estimate the effort of a new production ramp-up before the ramp-up. Further, the actions of the disturbance management speeded up the internal processes during the ramp-up. Overall, the production ramp-up was 16.9% ahead of the proposed time which was a success for the company. A possible extension of the model could include the series planning phase before the ramp-up and the transition to the later series production phase to achieve a more efficient complete product lifecycle. Furthermore, one can adapt recent research focusing on an integrative KPI network for ramp-up purposes [26].