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Title:Demand prediction and optimization of workshop manufacturing resources allocation: a new method and a case study
Authors:ID Wan, J. (Author)
Files:.pdf APEM17-4_413-424.pdf (957,39 KB)
MD5: 2C96FE06AA4058D81DB7FBD64603A224
 
URL https://apem-journal.org/Archives/2022/APEM17-4_413-424.pdf
 
Language:English
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:At present, great changes are taken place in the internal production management and resource allocation model of manufacturers. Under the premise of rational resource allocation, the completion period of products largely depends on the timeliness of resource allocation. The related studies mostly tackle the allocation of a single type of production resources in a single workshop, without considering much about the mutual influence between workshops. Through in-depth research on workshop manufacturing practices, this paper chooses to explore the planning, allocation, and demand prediction of manufacturing resources, which has long been a difficulty in workshop production. The research has great scientific research significance and practical value. The authors designed an algorithm based on the difference of the mean stagnation time of different production processes in the execution process, and used the algorithm to predict the number of production resources required in each period, before formulating the optimal configuration plan. This method is highly reasonable and applicable. After presenting a prediction method for the allocation demand of workshop manufacturing resources, the authors discussed whether the manufacturing resource allocation between different workshops is balanced in a fixed period. Then, a new idea was proposed for collaborative production between machines of different workshops in a specific environment, and an optimization algorithm was put forward to optimize the manufacturing resource allocation to machines facing the operation execution process. Through experiments, the authors compared the utilization rate of material, technological or human production resources in each period, and thereby verified the effectiveness of the proposed algorithm.
Keywords:manufacturing resources, resource demand, allocation, optimization, simulation, modelling, prediction
Publication status:Published
Publication version:Version of Record
Submitted for review:06.07.2022
Article acceptance date:15.10.2022
Publication date:30.09.2022
Publisher:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Year of publishing:2022
Number of pages:str. 413-424
Numbering:Vol. 17, no. 4
PID:20.500.12556/DKUM-97202 New window
UDC:658.51:004.8
ISSN on article:1854-6250
COBISS.SI-ID:269343491 New window
DOI:10.14743/apem2022.4.445 New window
Copyright:Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Publication date in DKUM:23.02.2026
Views:157
Downloads:1
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Categories:Misc.
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Record is a part of a journal

Title:Advances in production engineering & management
Shortened title:Adv produc engineer manag
Publisher:Fakulteta za strojništvo, Inštitut za proizvodno strojništvo
ISSN:1854-6250
COBISS.SI-ID:229859072 New window

Document is financed by a project

Funder:Wuhan Donghu University
Project number:2021dhsk005

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:proizvodnja, proizvodni viri, povpraševanje po virih, razporeditev virov, alokacija virov, optimizacija, simulacija, modeliranje, napovedovanje


Collection

This document is a part of these collections:
  1. Advances in production engineering & management

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