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result(s) for
"PRODUCTION MANAGEMENT"
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Key concepts in operations management
\"Over 50 concept entries include: Operations Strategy, Managing Innovation, Process Modeling, New Product Development, Forecasting, Planning and Control, Supply Chain Management, Risk Management and many more.\"--Publisher.
Digital twin-based smart production management and control framework for the complex product assembly shop-floor
2018
Digital twin technology is considered as a key technology to realize cyber-physical systems (CPS). However, due to the complexity of building a digital equivalent in virtual space to its physical counterpart, very little progress has been achieved in digital twin application, especially in the complex product assembly shop-floor. In this paper, we propose a framework of digital twin-based smart production management and control approach for complex product assembly shop-floors. Four core techniques embodied in the framework are illustrated in detail as follows: (1) real-time acquisition, organization, and management of the physical assembly shop-floor data, (2) construction of the assembly shop-floor digital twin, (3) digital twin and big data-driven prediction of the assembly shop-floor, and (4) digital twin-based assembly shop-floor production management and control service. To elaborate how to apply the proposed approach to reality, we present detailed implementation process of the proposed digital twin-based smart production management and control approach in a satellite assembly shop-floor scenario. Meanwhile, the future work to completely fulfill digital twin-based smart production management and control concept for complex product assembly shop-floors are discussed.
Journal Article
Capacity Allocation in Flexible Production Networks: Theory and Applications
by
Teo, Chung-Piaw
,
Zheng, Zhichao
,
Lyu, Guodong
in
Allocation
,
capacity configuration
,
Deliveries
2019
In many production environments, a fixed network of capacity is shared flexibly between multiple products with random demands. What is the best way to configure the capacity of the production network and to allocate the available capacity to meet predetermined fill rate requirements? We develop a new approach for network capacity configuration and allocation and characterize the relationship between the capacity of the network and the attainable fill rate levels for the products, taking into account the flexibility structure of the network. This builds on a new randomized allocation mechanism to deliver the desired services. We use this theory to investigate the connection between the flexibility structure and capacity configuration. We provide a new perspective to the well-known phenomenon that “long chain is almost as good as the fully flexible network”: for given target fill rates, the required capacity level in a long-chain network is close to that in a fully flexible network and is much lower than a dedicated system. We apply these insights and techniques on problems arising in the design of last-mile delivery operations and in semiconductor production planning, using real data from two companies.
This paper was accepted by Terry Taylor, operations management.
Journal Article
The Evolution of Closed-Loop Supply Chain Research
by
Van Wassenhove, Luk N.
,
Guide, V. Daniel R.
in
Analysis
,
Applied sciences
,
Cellular telephones
2009
The purpose of this paper is to introduce the reader to the field of closed-loop supply chains with a strong business perspective, i.e., we focus on profitable value recovery from returned products. It recounts the evolution of research in this growing area over the past 15 years, during which it developed from a narrow, technically focused niche area to a fully recognized subfield of supply chain management. We use five phases to paint an encompassing view of this evolutionary process for the reader to understand past achievements and potential future operations research opportunities.
Journal Article
Industry 4.0 implies lean manufacturing: research activities in industry 4.0 function as enablers for lean manufacturing
by
Sanders, Adam
,
Wulfsberg, Jens
,
Elangeswaran, Chola
in
Communications systems
,
cyber physical systems
,
Industry 4.0
2016
Purpose: Lean Manufacturing is widely regarded as a potential methodology to improve
productivity and decrease costs in manufacturing organisations. The success of lean
manufacturing demands consistent and conscious efforts from the organisation, and has to
overcome several hindrances. Industry 4.0 makes a factory smart by applying advanced
information and communication systems and future-oriented technologies. This paper analyses
the incompletely perceived link between Industry 4.0 and lean manufacturing, and investigates
whether Industry 4.0 is capable of implementing lean. Executing Industry 4.0 is a cost-intensive
operation, and is met with reluctance from several manufacturers. This research also provides an
important insight into manufacturers’ dilemma as to whether they can commit into Industry 4.0,
considering the investment required and unperceived benefits.
Design/methodology/approach: Lean manufacturing is first defined and different dimensions
of lean are presented. Then Industry 4.0 is defined followed by representing its current status in
Germany. The barriers for implementation of lean are analysed from the perspective of
integration of resources. Literatures associated with Industry 4.0 are studied and suitable solution
principles are identified to solve the above mentioned barriers of implementing lean.
Findings: It is identified that researches and publications in the field of Industry 4.0 held answers
to overcome the barriers of implementation of lean manufacturing. These potential solution principles prove the hypothesis that Industry 4.0 is indeed capable of implementing lean. It
uncovers the fact that committing into Industry 4.0 makes a factory lean besides being smart.
Originality/value: Individual researches have been done in various technologies allied with
Industry 4.0, but the potential to execute lean manufacturing was not completely perceived. This
paper bridges the gap between these two realms, and identifies exactly which aspects of Industry
4.0 contribute towards respective dimensions of lean manufacturing.
Journal Article