Semi-Generative Macro-Process Planning For Reconfigurable Manufacturing

2007 ◽  
pp. 251-258 ◽  
Author(s):  
Ahmed Azab ◽  
Giulio Perusi ◽  
Hoda A. ElMaraghy ◽  
Jill Urbanic
Author(s):  
Farayi Musharavati ◽  
Napsiah Ismail ◽  
Abdel Majid S. Hamouda ◽  
Abdul Rahman Ramli

Proses perancangan pembuatan adalah berkaitan dengan keputusan berdasarkan pemilihan tatarajah yang optimum daripada modul proses untuk pemprosesan bahagian kerja. Untuk pembentukan semula barisan pembuatan bagi pelbagai bahagian kerja, keputusannya dipengaruhi jenis proses yang sedia ada, hubungkait jujukan pemprosesan dan juga aturan pemprosesan bahagian kerja tersebut. Keputusan proses perancangan pembuatan mungkin bercanggah, oleh itu tugasan membuat keputusan perlu mengambil kira cara setemu. Kertas kerja ini membentangkan teknik optima untuk masalah berkaitan proses perancangan pembuatan dalam rangka kerja pembuatan pembentukan semula. Proses MPP dimodelkan sebagai masalah pengoptimuman dan keadah penyelesaian yang diperolehi daripada teknik metahuristik dikenali sebagai simulasi penyepuhlindapan. Fungsi analisis bagi memodel proses perancangan pembuatan adalah berdasarkan pengetahuan mengenai proses dan sistem pembuatan serta kekangan proses. Applikasi bagi pendekatan ini ditunjukkan melalui barisan pembuatan pembentukan semula berbilang tahap siri selari. Keputusan menunjukkan penambahbaik yang signifikasi diperolehi dalam penyelesaian untuk masalah jenis ini dengan menggunakan simulasi penyepuhlindapan. Tambahan pula, teknik metaheuristik berkebolehan untuk mengenal pasti kaedah proses pembuatan yang optima berdasarkan senario pengeluaran yang diberi. Kata kunci: Metaheuristik, simulasi penyepuhlindapan, proses perancangan pembuatan, sistem pembuatan pembentukan semula, senario pembuatan Manufacturing process planning (MPP) is concerned with decisions regarding selection of an optimal configuration for processing parts. For multiparts reconfigurable manufacturing lines, such decisions are strongly influenced by the types of processes available, the relationships for sequencing the processes and the order of processing parts. Decisions may conflict, hence the decision making tasks must be carried out in a concurrent manner. This paper outlines an optimization solution technique for the MPP problem in reconfigurable manufacturing systems (RMSs). MPP is modelled in an optimization perspective and the solution methodology is provided through a metaheuristic technique known as simulated annealing. Analytical functions for modelling MPP are based on knowledge of processes available to the manufacturing system as well as processing constraints. Application of this approach is illustrated through a multistage parallel–serial reconfigurable manufacturing line. The results show that significant improvements to the solution of this type of problem can be gained through the use of simulated annealing. Moreover, the metaheuristic technique is able to identify an optimal manufacturing process plan for a given production scenario. Key words: Metaheuristics, simulated annealing, manufacturing process planning, reconfigurable manufacturing systems, production scenarios


2015 ◽  
Vol 105 (04) ◽  
pp. 209-214
Author(s):  
A. Hees ◽  
K. Zellner ◽  
G. Reinhart

Zur Sicherung der Wettbewerbsfähigkeit in dynamischen Märkten müssen produzierende Unternehmen ihre Produktionssysteme in häufigen Intervallen anpassen. Ein Ansatz, diesen Herausforderungen zu begegnen, sind rekonfigurierbare Produktionssysteme (englisch: Reconfigurable Manufacturing Systems – RMS). Vorgestellt wird ein neuer Ansatz für die Produktionsplanung und -steuerung (PPS) in RMS – bestehend aus einem Datenmodell, einem Konfigurationsmanagement und einer Planungsmethode.   Manufacturing companies have to adapt their manufacturing systems in frequent and short intervals to secure their competitiveness in dynamic markets. One approach to ensure companies’ success are Reconfigurable Manufacturing Systems (RMS). In this context, a new approach for production planning (PPC) in RMS, consisting of a data model, a configuration management and a planning method, is described in this paper.


2011 ◽  
Vol 213 ◽  
pp. 9-14
Author(s):  
Shi Gang Song ◽  
Xia Xia Hu ◽  
Jian Liu

For dynamic process planning under reconfigurable manufacturing system (RMS), the method of process planning based on similarity theory was presented. Part feature description was built as well as case index structure. Procedure combination principia suited for reconfigurable machine tool (RMT) and sort rule based on relation among features were given. Similarity process information was created by comparability judgment of part feature multiple-tree, procedure was combined by the agglomerative hierarchical clustering method, and every working-step was sorted in procedure group. Moreover, the process planning system was developed with Visual C++ and verified through example test.


Author(s):  
Moon Jung Chung ◽  
Patrick Kwon ◽  
Brian Pentland ◽  
Sangchul Kim

A new approach to enacting processes “on the fly” by the participants is proposed for collaborative manufacturing. This approach allows the selection and planning of processes at a higher level as mutiple participants around the world can theoretically engage in planning the processes. Reconfigurable manufacturing system in such scenario means the selection of an appropriate sequence of processes, the process planning of the selected processes and the assignment of appropriate resources to carry out the processes. To achieve that, it requires a new method of representing, sharing and executing process information. In addition, the representation of organizations providing the services and their resources is the prerequisite to the problems we intend to resolve. Thus, rather than applying it to develop a new process planning, this paper proposes this system to connect, share, and reconfigure the network of manufacturing and design companies who are collaborating for a common project. Our system called MIDAS provides functionalities for the representation of processes including alternatives, the planning of resources and the execution of process. Moreover, MIDAS uses XML to encode the process grammar, constraints and other business, design and manufacturing logic, facilitating scalability required for large-scale collaboration.


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