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Demand Responsive Planning: A dynamic and responsive planning framework based on workload control theory for cyber-physical production systems
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. (Technologies for Adaptable Production)ORCID iD: 0000-0002-6607-9634
2015 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Recent developments in the area of Cyber-Physical Production Systems prove that high technology readiness level is already achieved and industrialization of such technologies is not far from today. Although these technologies seem to be convenient in providing solutions to environmental uncertainties, their application provides adaptability only at shop floor level. Needless to say, an enterprise cannot reach true adaptability without ensuring adaptation skills at every level in its hierarchy. Commonly used production planning and control approaches in industry today inherit from planning solutions which are developed in response to historical market characteristics. However, market tendency in recent years is towards making personalized products a norm. The emerging complexity out of this trend obliges planning systems to a transition from non-recurring, static planning into continuous re-planning and re-configuration of systems. Therefore, there is a need of responsive planning solutions which are integrated to highly adaptable production system characteristics.

In this dissertation, Demand Responsive Planning, DRP, is presented which is a planning framework aiming to respond to planning needs of shifting trends in both production system technologies and market conditions. The DRP is based on three main constructs such as dynamicity, responsiveness and use of precise data. These features set up the foundation of accomplishing a high degree of adaptability in planning activities. By this means, problems from an extensive scope can be handled with a responsive behavior (i.e. frequent re-planning) by the use of precise data. The use of precise data implies to execute planning activities subject to actual demand information and real-time shop floor data. Within the context of the DRP, both a continuous workload control method and a dynamic capacity adjustment approach are developed. A test-bed is coded in order to simulate proposed method based on a system emulation reflecting the characteristics of cyber-physical production systems at shop floor level.

Continuous Precise Workload Control, CPWLC, method is a novel approach aiming at precise control of workload levels with the use of direct load graphs. Supported by a multi-agent platform, it generates dynamic non-periodic release decisions exploiting real time shop floor information. As a result, improved shop floor performances are achieved through controlling workload levels precisely by the release of appropriate job types at the right time.

Presented dynamic capacity adjustment approach utilizes rapid re-configuration capability of cyber-physical systems in achieving more frequent capacity adjustments. Its implementation architecture is integrated to the CPWLC structure. By this means, a holistic approach is realized whereby improved due date performance is accomplished with minimized shop floor congestion. Hence, sensitivity to changing demand patterns and urgent job completions is improved.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. , xvi, 217 p.
Series
TRITA-IIP, ISSN 1650-1888 ; 15:04
Keyword [en]
Demand responsive planning, continuous workload control, cyber-physical production systems, evolvable production systems, dynamic capacity adjustment
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Engineering and Management; SRA - Production; Planning and Decision Analysis
Identifiers
URN: urn:nbn:se:kth:diva-172969ISBN: 978-91-7595-673-2 (print)OAI: oai:DiVA.org:kth-172969DiVA: diva2:851184
Public defence
2015-09-24, M311, Brinellvägen 68, KTH, Stockholm, 09:00 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme
Note

QC 20150907

Available from: 2015-09-07 Created: 2015-09-03 Last updated: 2016-03-15Bibliographically approved

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