A Petri Net Technique for Batch Delivery Time Estimation

Xirouchakis, Paul; Kiritsis, Dimitris; Günther, Christian; Persson, Jan-Gunnar

doi:10.1016/s0007-8506(07)63202-8

Cited by 8 publications

(6 citation statements)

References 6 publications

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“…This algorithm has an incremental nature and calculates the optimum process planning cost directly, which means there is no need to develop all possible solutions first. A year later, Xirouchakis et al [146] applied Petri net in non-linear process planning to estimate the delivery time and cost of a batch of manufactured mechanical parts. In comparison with the previous work, the interleaving of transitions is allowed in the new method.…”

Section: Estimate the Time And The Cost To Manufacture The Partmentioning

confidence: 99%

A survey on smart automated computer-aided process planning (ACAPP) techniques

Al-wswasi

Ivanov

Makatsoris

2018

Int J Adv Manuf Technol

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The concept of smart manufacturing has become an important issue in the manufacturing industry since the start of the twenty-first century in terms of time and production cost. In addition to high production quality, a quick response could determine the success or failure of many companies and factories. One the most effective concepts for achieving a smart manufacturing industry is the use of computer-aided process planning (CAPP) techniques. Computer-aided process planning refers to key technology that connects the computer-aided design (CAD) and the computer-aided manufacturing (CAM) processes. Researchers have used many approaches as an interface between CAD and CAPP systems. In this field of research, a lot of effort has been spent to take CAPP systems to the next level in the form of automatic computer-aided process planning (ACAPP). This is to provide complete information about the product, in a way that is automated, fast, and accurate. Moreover, automatic feature recognition (AFR) techniques are considered one of the most important tasks to create an ACAPP system. This article presents a comprehensive survey about two main aspects: the degree of automation in each required input and expected output of computer-aided process planning systems as well as the benefits and the limitations of the different automatic feature recognition techniques. The aim is to demonstrate the missing aspects in smart ACAPP generation, the limitations of current systems in recognising new features, and justifying the process of selection.

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Section: Estimate the Time And The Cost To Manufacture The Partmentioning

confidence: 99%

A survey on smart automated computer-aided process planning (ACAPP) techniques

Al-wswasi

Ivanov

Makatsoris

2018

Int J Adv Manuf Technol

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“…However, a weak point of the queuing models is the fact that it is impossible to investigate break-down situations and repairs of particular elements of the system (subsystems). The most common method used for the assessment of parameters of flexible manufacturing system is discrete simulation, and the most suitable tools used for discrete simulation are Petri networks [3][4][5][6][7][11][12][13] which allow to analyze technological manufacturing structures understood as systems. The modeling process with the use of Petri network can be easily assimilated due to the graphic nature (bipartite, directed graph) as well as the parallel and dynamic nature of manufacturing systems.…”

Section: Flexible Manufacturing Systemsmentioning

confidence: 99%

“…For the modelling, we accept the basic form of Petri network of the class P/T in which [7,[11][12][13]:…”

Section: Network Model Of the Systemmentioning

confidence: 99%

Modeling of manufacturing systems and robot motions

Köst¹,

Zdanowicz²

2005

Journal of Materials Processing Technology

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“…This period was followed by a range of significant applications of Petri networks in modeling discrete manufacturing processes. The team of Kiritsis has showed particular interest in this issue [3][4][5][6][7][8][9][10]. The published works analyzed the opportunities of classifying operations in the process of production, representation of alternative courses of manufacturing process and dynamic planning of processes.…”

Section: Introductionmentioning

confidence: 99%

“…The Petri networks methodology is also used here. The work [10] considering the issue of estimating the upper and lower limit of time and cost of completing a production series of a given part in certain workshop conditions is essential here. An opportunity of variant course of individual processes for individual parts of a production batch is assumed.…”

Section: Introductionmentioning

confidence: 99%

Petri Networks in the Planning of Discrete Manufacturing Processes

Stryczek¹

2018

Petri Nets in Science and Engineering

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This chapter puts forward characteristics of selected issues of manufacturing processes planning using the Petri networks technique. It includes references to the extensive literature concerning the use of Petri networks in computer aided planning of discrete production processes. Diversity of these problems is high as it refers both to the methods of modeling and simulation of the course of manufacturing processes, the issue of optimizing these processes and production systems, representation of knowledge on production parts of equipment and integration of planning and production activities in general. The work puts forward example use of a temporary, priority Petri network for modeling and optimizing production systems and manufacturing operations as well as an example of fuzzy interference using the Petri network mechanism.

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A Petri Net Technique for Batch Delivery Time Estimation

Cited by 8 publications

References 6 publications

A survey on smart automated computer-aided process planning (ACAPP) techniques

A survey on smart automated computer-aided process planning (ACAPP) techniques

Modeling of manufacturing systems and robot motions

Petri Networks in the Planning of Discrete Manufacturing Processes

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