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Theory Building Approach

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Part of the Springer Series in Advanced Manufacturing book series (SSAM)

Abstract

The network nature of manufacturing may not be captured by further detailing the systems thinking. The scope has to be widened up. To speed up research progresses, the base for further grounded theory has to be strengthened and the role of outside disciplines for manufacturing has to be newly established in order to profit from the catalysing forces and fruitful impacts of other disciplines’ work. Research work at the intersections of disciplines, changing the core of manufacturing by intensive interaction, necessitates theory building on the base of a unified language. Mathematical topology may be identified as accountable discipline, as it offers adequate abstractions as well as the explicative power to capture the relevant manufacturing contexts and objects. The Hausdorff space with its attached spaces and the respective mappings perfectly translate the Cyber Physical Production Systems into theory and application likewise. Moreover, it smoothly harmonises the relevant models that are applied for effective virtualisations of manufacturing processes, as aimed at. The resulting framework captures all network principles and smart unit properties, and lays ground for standardisation efforts.

Keywords

  • System Thinking
  • Theory Building
  • External Theory
  • Bullwhip Effect
  • Manufacturing Network

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Fig. 3.1
Fig. 3.2

Notes

  1. 1.

    The numerous alternative definitions for the term “theory”, each of them highlighting specific aspects and emphasising distinct points of view, have all in common that a theory is represented by a set of laws linked by related derivations. For example, the Popperian as well as the Carnapian Schools see theories as sets of statements: scientific theories are general theses and statements that are, as any representation, symbols and systems of characters (Popper 1982). Similar thinking is provided by Sutton and Staw (1995), who regard ‘theory’ as a set of logically interconnected arguments that tell a story about why certain acts, events, structures and thoughts occur. So, theories do not just ascertain practical insights, theories are considered the bases of all science. And establishing powerful theories is crucial to any scientific progress, but they are also subject to discourse (Foucault 1969). Returning to our line of reasoning, the development of appropriate theories brought considerable progress for manufacturing sciences. A case in point is the broadening material transformations to the total organisational design of manufacturing companies by establishing the Tayloristic thinking, that could later be embedded in the General Systems Theory (Bertalanffy 1973). New ways of modelling, e.g. by interpreting technical transformation as inputs and outputs, allowed deeper insight into the logic of manufacturing organisations and its implications to integration of aspects, decomposition for analysis and appropriate control mechanisms. The resulting thoughts actually are indispensable constituents of all current manufacturing systems’ theories.

  2. 2.

    Moreover, there are debates within this context, seriously putting into question scientific specializations and differentiations of disciplinary knowledge as barriers of science and knowledge in total that can be overcome by means of interdisciplinarity (Mittelstraß 1987).

  3. 3.

    In that context, science may be named any intersubjectively verifiable examination of facts, including their systematic descriptions and—if possible—their explications (Carnap 1966). With an identified object of interest as a starting point, any science traditionally strives for understanding and principles in line with specificities of the associated branch of knowledge, also referred to as the accounting scientific discipline within the relevant classification of sciences (Popper 1959). Well-established scientific disciplines have considerable impact on research. The content of theory to be proven seems to strongly depend on presumptions, experiential evidence and ad hoc explanations that constitute scientific progress, however always tightly held together by a dominant paradigm that may as well be referred to as the identity of the accounting discipline. In this perspective, we speak of a pure discipline or of mono-disciplinarity if a certain domain is scientifically permeated with a consistent paradigmatic and theory-rich concept.

  4. 4.

    Theory building, e.g. (Weick 1995), in general, occurs through distinct procedures, as induction, deduction, comparative analysis or theoretical sampling within a discipline and eventually the formation of further reaching theories (Glaser and Strauss 1967; Suddaby 2006). In such instance, principles of abstraction (Dekkers 2013; Timpf 1999)—classification, aggregation and generalisation—will support the extension of principles and solutions to become underpinning theories. With formations as e.g. Holonic Manufacturing or Soft Artefact, valuable scientific qualities came to light to be theorised, in synthesis with complexity theories and life-cycle approaches. Similarly, skilled conjectures for network manufacturing will cumulate insights into adequate frameworks more swiftly and more coherently through engaging with more widely accepted impactful models embracing strong bodies of (ready for use) knowledge.

  5. 5.

    Without going into further details, it can be stated that topology has had an impact manufacturing networks’ research already. By introducing topology, many portions of manufacturing theories (e.g. generic elements, models and principles for social agents as well as software agents’ network interactions) were reframed; other elements permit designing novel steadily evolving network decision modes and such set-up facilitates exploiting the networks’ characteristics related to cooperative games and partnership for value optimisation. These examples of topology influence stand for quite a number of effects that have been observed around Manufacturing Networks.

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Kühnle, H., Bitsch, G. (2015). Theory Building Approach. In: Foundations & Principles of Distributed Manufacturing. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-319-18078-6_3

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  • DOI: https://doi.org/10.1007/978-3-319-18078-6_3

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