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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : CIRP Journal of Manufacturing Science and Technology, Volume 6, Issue 4, 2013, Pages 274–280
Due to fast changing market requirements and short product life cycles, flexibility is one of the crucial characteristics of automated and partly automated assembly systems besides purchasing and operation costs. Since the life cycle of an assembly system is longer than the one of the assembled products, flexibility enables an assembly system to adapt to future product requirements as well as production scenarios. The approach proposed in this paper strives for a systematic and economic measurement of flexibility in investment decisions. It offers methods and key-figures supporting the investment decisions for automated assembly systems. The right levels of flexibility and automation of an assembly system are evaluated by using a set of potential future scenarios of the system's life cycle. Based on two new key-figures called Return on Automation and Return on Flexibility, the approach allows comparing different configurations of an assembly system and therefore supports well-informed investment decisions.
Companies in manufacturing industries are confronted with the challenges of an increasing market dynamic, an increasing competition and an uncertain environment, caused by globalization of the markets and economic crises. Shorter product lifecycles, more product variants and volatile product demands and a concurrent increasing product complexity, are characteristic consequences for companies in this market environment (Schuh et al., 2004, Schuh et al., 2005 and Seidel and Garrel, 2011). In this context, the ability to adapt to the changing requirements is becoming an important competitive factor. A continuous adaptation of the manufacturing system to the market requirements is necessary. Since future requirements for the manufacturing system cannot be forecasted exactly, a proactive adaptation of the system is rarely possible and the manufacturing system is not optimally configured for the upcoming situation. Therefore, manufacturing flexibility is an important goal to achieve in the early planning phases of the system (Schuh et al., 2004 and Schuh et al., 2005). In addition low production costs are an important factor for competitiveness. The automation of manufacturing systems is one solution to reach this goal. While automation usually effects a reduction of flexibility of the manufacturing system, a trade-off has to be made between these two goals. The approach proposed in this paper, attempts to give support in identifying the right trade-off between flexibility and automation in investment decisions for automated assembly systems. Automated assembly systems are an example for systems with high investment costs on the one hand and the need for flexibility over the system's life cycle on the other hand. The approach is intended to be used in early planning phases of automated assembly systems. Chapter two of this paper illustrates the required types of flexibility of assembly systems. Challenges in the economic evaluation of flexibility and existing approaches are summarized in chapter three. In chapter four the approach to a life cycle oriented evaluation of flexibility in investment decisions for automated assembly systems is introduced. In chapter five an industry case is presented. Chapter six concludes this paper.
نتیجه گیری انگلیسی
Because of increasing market dynamics and competition, companies in the manufacturing industry have to consider the flexibility of their manufacturing system in early planning phases and especially in investment decisions. The approach proposed in this paper is capable of coping with the challenge of evaluating flexibility of assembly systems in investment decisions. This paper introduces the two main aspects of the approach: • Definition of the key-figures Return on Automation (ROA) and Return on Flexibility (ROF). • Introduction of the method for evaluating flexibility in investment decisions. Further on, an application in an industry case has verified the relevance and potential of the approach. The challenges within the new approach will be on the one hand the implementation of the method within an IT-application and on the other hand, the integration of such an application into the structure of existing companies’ decision processes. The IT-application has to provide different tools. A calculation tool, tools for the definition of different scenarios and for the estimation of their likelihoods, as well as a tool for the flexibility check of the system are essential. To ensure an easy integration of the IT-application within a company, a central server with different front-end types is one possibility for an implementation of the approach. An efficient collection of the necessary data, supporting a good cost/benefit ratio, is very important for the integration of the application. Therefore, a standardized application for the data collection is required. On the one hand, this data collection application has to be able to cope with different data sources like ERP-systems, existing databases, or companies’ experts. On the other hand, the data collection application has to be able to select data in the right quality, which is essential for the evaluating approach. The data collector module suggested by Georgoulias et al. (2009) is an example for a data collection application. The proposed approach is capable of evaluating volume, mix and product flexibility of automated assembly systems and supports companies investment decision.