Methodik zur Planung und Konfigurationsauswahl skalierbarer Montagesysteme - Ein Beitrag zur skalierbaren Automatisierung

Abstract

Modern production systems must be able to react to the uncertain and volatile requirements resulting from short product life cycles and personalized customer requests. Changeable systems are needed, that can adapt to these changing requirements and achieve similar cost efficiency as traditional lean production systems. Especially in high-wage countries Scalable Automation is a key prerequisite to reach this cost-efficiency. Scalable Automation allows a quick increasement or decreasement of the level of automation of an assembly system. There are different technical and organizational possibilities for the implementation of changeable assembly systems. The right assembly stations and the optimal change enablers for minimizing the life cycle costs of an assembly system must be found. In order to identify effective change enablers it is neccessary to develop concepts for changeable production equipment with different levels of automation, at an early stage. The aim of this dissertation is to derive technical measures for achieving the optimal changeability of an assembly system. For this purpose, the optimal changeability is measured on the basis of the expected life cycle costs of the assembly system. The considered changeability focuses on Scalable Automation. The methodology of deriving technical measures for achieving the optimal changeability consists of four steps. First step is the quantification of volatility and uncertainty based on change drivers influencing specific receptor key performance indicators (receptor KPIs). In the second step the technical solution space of possible physical configurations of the system is developed. In order to calculate a scaling strategy a Markov decision problem is formulated and solved in the third step. The fourth step consists of the analysis of the scaling strategy and the derivation of construction guidelines for specific change enablers in order to find technical measures for achieving the optimal changeability. The methodology is explained using the example of the Learning Factory Global Production of the wbk Institute of Production Science. For verification purposes, the methodology is applied to the case of a manufacturer of high pressure valves for the use in mobile fuel cells. In order to carry out the necessary calculations the application SkaliA has been developed.