A Versatile and Scalable Production Planning and Control System for Small Batch Series
The importance of flexibility in modern production and manufacturing systems increases in face of a constant rising degree of individualization in manufacturing industry and simultaneously shorter product life cycles. A result is a high number of variants
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1 Introduction Most of today’s companies are faced with the increasing need to operate effectively and efficiently. Since many business parameters are less predictable, the global markets became more dynamic, traditional ways of designing and operating production, and logistics systems are not able to handle these new challenges anymore. These challenges are mainly driven by the globalization of supply chains, shorter product cycles, mass customization, and the rising speed of delivery [12, 26, 30]. All these changes are affecting the company organization and logistics. In this chapter, the automotive industry is considered as the application domain. Nowadays, mass-market vehicles are commonly produced with a continuous flow manufacturing system that consists of a combination of highly efficient production and assembly lines. In a broader sense, all vehicles follow the same designated sequence A. Böckenkamp ⋅ F. Weichert Department of Computer Science VII, Technical University of Dortmund, Otto-Hahn-Str. 16, 44227 Dortmund, Germany e-mail: [email protected] F. Weichert e-mail: [email protected] C. Mertens ⋅ C. Prasse (✉) ⋅ J. Stenzel Fraunhofer Institute for Material Flow and Logistics, Joseph-von-Fraunhofer-Str. 2-4, 44227 Dortmund, Germany e-mail: [email protected] C. Mertens e-mail: [email protected] J. Stenzel e-mail: [email protected] © Springer International Publishing Switzerland 2017 S. Jeschke et al. (eds.), Industrial Internet of Things, Springer Series in Wireless Technology, DOI 10.1007/978-3-319-42559-7_22
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of production steps until they are readily assembled. A centralized production planning and controlling approach enables a smooth production flow through the described system but requires significant investment in IT infrastructure and production equipment. Additionally, the approach is best suited for deterministic customer demands which do not exist at all times and in all markets [2, 31]. New trends within the automotive industry, such as the launch of electric vehicles and various technologies in the field of Industry 4.0 [4], challenge existing production systems. Specifically, these challenges include an increased need for flexibility through volatile selling markets, unforeseeable technological developments (e.g., in the field of electric vehicles), shorter production cycles, and the increasing individualization of products [13, 22, 23, 31]. Following the vision of Industry 4.0 (cf. Sect. 1.1), these challenges could be resolved through the concept of smart factories. These factories are scalable and operate at high flexibility through decentralized control strategies, like Multi Agent System (MAS) approaches for material flow and program planning, and the utilization of technologies such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS), refer to [4, 32]. Within the scope of these smart factories, the decentralized program planning approach as well as the application of CPS t
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