Modeling and Analyzing the Material Flow of Crowdsourcing Processes in Cloud-Based Manufacturing Systems Using Stochastic Petri Nets

2014 ◽  
Author(s):  
Dazhong Wu ◽  
David W. Rosen ◽  
Dirk Schaefer
Keyword(s):  
Petri Nets ◽  
Material Flow ◽  
Manufacturing Systems ◽  
Cloud Manufacturing ◽  
Stochastic Petri Nets ◽  
Manufacturing Processes ◽  
Manufacturing Enterprises ◽  
Car Suspension ◽  
Manufacturing Performance

Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, has the potential to allow manufacturing enterprises to be rapidly scaled up and down by crowdsourcing manufacturing tasks or sub-tasks. To improve the efficiency of the crowdsourcing process, the material flow of CBM systems needs to be managed so that several manufacturing processes can be executed simultaneously. Further, the scalability of manufacturing capacity in CBM needs to be designed, analyzed, and planned in response to rapidly changing market demands. The objective of this paper is to introduce a stochastic petri nets (SPNs)-based approach for modeling and analyzing the concurrency and synchronization of the material flow in CBM systems. The proposed approach is validated through a case study of a car suspension module. Our results have shown that the SPN-based approach helps analyze the structural and behavioral properties of a CBM system and verify manufacturing performance.

Scalability Planning for Cloud-Based Manufacturing Systems

2015 ◽  
Vol 137 (4) ◽  
Author(s):  
Dazhong Wu ◽  
David W. Rosen ◽  
Dirk Schaefer
Keyword(s):  
Resource Sharing ◽  
Material Flow ◽  
Manufacturing Systems ◽  
Service Providers ◽  
Cost Effective ◽  
Stochastic Petri Nets ◽  
Third Party ◽  
System Capacity ◽  
Manufacturing Performance ◽  
Manufacturing Resource

Cloud-based manufacturing (CBM) has recently been proposed as an emerging manufacturing paradigm that may potentially change the way manufacturing services are provided and accessed. In the context of CBM, companies may opt to crowdsource part of their manufacturing tasks that are beyond their existing in-house manufacturing capacity to third-party CBM service providers by renting their manufacturing equipment instead of purchasing additional machines. To plan manufacturing scalability for CBM systems, it is crucial to identify potential manufacturing bottlenecks where the entire manufacturing system capacity is limited. Because of the complexity of manufacturing resource sharing behaviors, it is challenging to model and analyze the material flow of CBM systems in which sequential, concurrent, conflicting, cyclic, and mutually exclusive manufacturing processes typically occur. To address and further study this issue, we develop a stochastic Petri nets (SPNs) model to formally represent a CBM system, model and analyze the uncertainties in the complex material flow of the CBM system, evaluate manufacturing performance, and plan manufacturing scalability. We validate this approach by means of a delivery drone example that is used to demonstrate how manufacturers can indeed achieve rapid and cost-effective manufacturing scalability in practice by combining in-house manufacturing and crowdsourcing in a CBM setting.

scholarly journals Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Vladimir Modrak ◽  
Zuzana Soltysova
Keyword(s):  
Manufacturing Process ◽  
Material Flow ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Flow Shop ◽  
Manufacturing Processes ◽  
Process Chains

Manufacturing systems can be considered as a network of machines/workstations, where parts are produced in flow shop or job shop environment, respectively. Such network of machines/workstations can be depicted as a graph, with machines as nodes and material flow between the nodes as links. The aim of this paper is to use sequences of operations and machine network to measure static complexity of manufacturing processes. In this order existing approaches to measure the static complexity of manufacturing systems are analyzed and subsequently compared. For this purpose, analyzed competitive complexity indicators were tested on two different manufacturing layout examples. A subsequent analysis showed relevant potential of the proposed method.

Efficient Simulation and Parametrization of Stochastic Petri Nets in SystemC: A Case study from Systems Biology

2019 ◽  
Author(s):  
Simone Caligola ◽  
Tommaso Carlucci ◽  
Franco Fummi ◽  
Carlo Laudanna ◽  
Gabriela Constantin ◽  
...  
Keyword(s):  
Systems Biology ◽  
Petri Nets ◽  
Stochastic Petri Nets ◽  
Efficient Simulation

scholarly journals A Smart Cloud-Based System for the WEEE Recovery/Recycling

2014 ◽  
Author(s):  
Xi Vincent Wang ◽  
Brenda N. Lopez N. ◽  
Lihui Wang ◽  
Jinhui Li ◽  
Winifred Ijomah
Keyword(s):  
Manufacturing Systems ◽  
Service Oriented Architecture ◽  
Intelligent System ◽  
Hazardous Materials ◽  
Cloud Manufacturing ◽  
Data Management System ◽  
Manufacturing Processes ◽  
Component Level ◽  
Recovery System ◽  
Service Oriented

Waste Electrical and Electronic Equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus it is necessary to develop a distributed and intelligent system to support WEEE recovery and recycling. In recent years, the Cloud concept has gained increasing popularity since it provides a service-oriented architecture that integrates various resources over the network. Cloud Manufacturing systems are proposed world-wide to support operational manufacturing processes. In this research, Cloud Manufacturing is further extended to the WEEE recovery and recycling context. A Cloud-based WEEE Recovery system is developed to provide modularized recovery services on the Cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also proposed with the help of the Quick Respond code method.

scholarly journals Cloud Manufacturing Concept as a Tool of Multimodal Manufacturing Systems Integration

2012 ◽  
Vol 4 (1) ◽  
pp. 17-42 ◽  
Author(s):  
Grzegorz Kłosowski
Keyword(s):  
Manufacturing Systems ◽  
Process Integration ◽  
Negative Impact ◽  
Cloud Manufacturing ◽  
Manufacturing Processes ◽  
Production Processes ◽  
Production Models ◽  
Multimodal Systems ◽  
Novel Approach ◽  
Increasing Demand

Abstract The following article deals with a novel approach to manufacturing in the context of the increasing demand for system and process integration. This integration chiefly applies to concrete facets of manufacturing tasks which must be taken into consideration in the stage of planning and preparation for complex production processes. Those facets are primarily exemplified by order types (such as production, service and cooperative commissions etc.), production models (e.g. discrete and process modeling), product categorization based on established criteria (e.g. production technology, complexity level, used materials and extras, weight, etc.) as well as many other aspects that hold great significance in the automatization of manufacturing processes. When more advanced orders are to be realized, one of the main challenges posed by this situation is the need to accomplish multiple operations which due to their different nature, scope and scale (e.g. varied processing types: heat and plastic treating, machining etc.) have to be conducted by different contractors. In order to address those key problems and reduce the negative impact of multimodality, the author proposes a manufacturing cloud (also known as cloud manufacturing) which is a variant of a groundbreaking, yet well-established concept - cloud computing. This paper presents the chief notions of this method created specifically with integrated multimodal systems and production processes. The author also highlights key problems that should be addressed before this solution can be used in practice.

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