Complexity reduction in engineer-to-order industry through real-time capable production planning and control

The engineer-to-order industry is under constant pressure to optimise production and handle complexity in the delivery of the right components at the right time. In many cases, e.g. in the building industry, they have to install their components at the construction site. Synchronisation between fabr...

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Bibliographic Details
Published inProduction engineering (Berlin, Germany) Vol. 12; no. 3-4; pp. 341 - 352
Main Authors Rauch, Erwin, Dallasega, Patrick, Matt, Dominik T.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2018
Springer Nature B.V
Subjects
Combinatorial analysis
Complexity
Construction industry
Construction sites
Digitization
Engineering
Engineers
Industrial and Production Engineering
Production
Production Management
Production planning
Real time
Reduction
Software development tools
Time dependence
Value engineering
Production planning and control
Industry 4.0
Real-time capability
Engineer-to-order
Axiomatic design
Complexity
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Summary:The engineer-to-order industry is under constant pressure to optimise production and handle complexity in the delivery of the right components at the right time. In many cases, e.g. in the building industry, they have to install their components at the construction site. Synchronisation between fabrication and on-site installation is difficult to realise with traditional planning techniques and instruments. The purpose of this study is to outline the potential of real-time-capable production planning and control in engineer-to-order companies as a successful approach to minimise time-dependent combinatorial complexity in the value chain. This research is based on axiomatic design theory in order to explain and confirm the hypothesis of complexity reduction through a near real-time feedback request at the installation site. We have demonstrated this through the information axiom of axiomatic design which states that complexity can be reduced to a minimum through a digitally automated continuous (re-)planning in order to avoid the system range shifting outside of the design range. Thus, the research team has described the first results of an industrial case study to develop a digital software tool to overcome this limitation. Our research contributes to complexity management in engineer-to-order manufacturing companies and further provides future direction towards digitalisation.
ISSN:0944-6524
1863-7353
DOI:10.1007/s11740-018-0809-0