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http://yadda.icm.edu.pl:443/baztech/element/bwmeta1.element.baztech-801da609-2374-40e9-858d-0f3e17a66d03

Czasopismo

Journal of Achievements in Materials and Manufacturing Engineering

Tytuł artykułu

Application of quality engineering techniques in the main domains of industrial engineering

Autorzy Karimi Gavareshki, M.H.  Abbasi, M.  Karbasian, M.  Rostamkhani, R. 
Treść / Zawartość http://www.journalamme.org
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Purpose: of this paper is to cover the main domains of industrial engineering based on the statistical and non-statistical techniques related to quality engineering. In this research, in addition to the review of the main domains of industrial engineering and the required specifications of technique, have been tried to present an integrated model of application of these techniques in order to create or increase the total score of productivity and sustainability in related scale with Analytic Hierarchy Process (AHP) approach. Design/methodology/approach: of this paper has been divided in two categories. The method of theoretical research consists of data collection tools, reference books, and several articles of the Iranian Center for Defences Standard. The method of practical research is the assessment of selected statistical and non-statistical techniques related to quality engineering, which have been deployed in the main domains of industrial engineering related to the manufacturing factories that are belonged to the selected industries of the Defence Industries Organization (DIO). Findings: of this paper consist of four main results. The maximum impact of standard statistical techniques in order to cover the main domains of industrial engineering and the required specifications of technique is related to the Statistical Process Control (SPC). Furthermore, the maximum impact of non-statistical techniques in order to cover them, is related to the Quality Function Deployment (QFD). The other results, which can be assessed with details, have shown that the maximum importance of the main domains of industrial engineering is related to the planning and manufacturing control and the maximum importance of the required specifications of technique is related to the mathematical analysis too. The total score of productivity and sustainability in related scale has been achieved to the upper than moderate level. In this research, the identification and determination of important factors, which have influenced on the productivity and sustainability have been done for the first time. The percentage of impact of the quality engineering techniques for both productivity and sustainability in the industrial engineering field is approximate to 70%. Research limitations/implications: of this paper suggest that the application of quality engineering tools including statistical and non-statistical techniques can be generalized to the other engineering or management fields with the same Analytic Hierarchy Process (AHP) or Analytic Network Process (ANP) approach in phase environments. Originality/value: of this paper have been extracted from the managers and experts involved with qualitative issues in the different levels of the Defence Industries Organization (DIO) and the Maham Group. This values are assessed from two aspects. Firstly, the validity of this research was carried out using expert’s opinions (Industrial advisers, Lead auditors of the Iranian center for Defences Standard and university professors). Secondly, all values of the research reliability are acceptable.
Słowa kluczowe
PL inżynieria produkcji   inżynieria jakości   techniki statystyczne  
EN industrial engineering   quality engineering   statistical techniques   non-statistical techniques  
Wydawca International OCSCO World Press
Czasopismo Journal of Achievements in Materials and Manufacturing Engineering
Rocznik 2018
Tom Vol. 90, nr 1
Strony 22--40
Opis fizyczny Bibliogr. 20 poz., rys, tab., wykr.
Twórcy
autor Karimi Gavareshki, M.H.
  • Complex of Management and Soft Technologies, Malek-Ashtar University of Technology, Tehran, Iran
autor Abbasi, M.
  • Complex of Management and Soft Technologies, Malek-Ashtar University of Technology, Tehran, Iran
autor Karbasian, M.
  • Department of Industrial Engineering, Malek-Ashtar University of Technology, Esfahan, Iran
autor Rostamkhani, R.
Bibliografia
[1] K. Rezaei, Using of the Quality Engineering Techniques in the Framework of Quality Management systems, Proceedings of the 2nd International Quality Management Conference, Tehran, Iran, 2001, CQM02 – 002 (in Farsi)
[2] D. Bounazef, C. Chabani, A. Idir, M. Bounazef, Management Analysis of Industrial Production Losses by the Design of Experiments, Statistical Process Control, and Capability Indices, Journal of Business and Management 2/1 (2014) 65-72.
[3] C. Fisher, New Techniques in Project Management, American Journal of Industrial and Business Management 4/12 (2014) 739-750.
[4] M.H. Karimi Gavareshki, M. Sharifi Zamani, R. Rostamkhani, Identification and Determination of Effective Application of Statistical Prioritize Techniques in Quality Management System in Defence Industries Organization, Iranian Electric Industry Journal of Quality and Productivity 2/4 (2014) 18-29 (in Farsi)
[5] M. Abbasi, R. Rostamkhani, Reliability Application of Industrial Manufacturing Networks in Outsourcing, Journal of Engineering and Quality Management 3/4 (2014) 247-259 (in Farsi).
[6] X. Zhou, Mechanism Design Theory: The Development in Economics and Management, Journal of Business and Management 4/2 (2016) 345-348.
[7] S. Rezazadeh, A. Jahani, M. Makhdoum, H.G. Meigooni, Evaluation of the Strategic Factors of the Management of Protected Areas Using SWOT Analysis, Journal of Ecology 7/1 (2017) 55-68.
[8] M.H. Karimi Gavareshki, M. Abbasi, R. Rostamkhani, Application of QFD and VE and Lean Approach for Control Tests in a Product Design, Archives of Materials Science and Engineering 84/2 (2017) 65-78.
[9] T. Depoo, G.D. Shanmuganathan, An Empirical Investigation on Leadership Styles Applied for Global Brand Management of Multinational Organizations in the United States, Journal of Business and Management 1/2 (2013) 11-17.
[10] A.J.G. Silvius, R.P.J, Schipper, Sustainability in Project Management Competencies: Analysing the Competence Gap of Project Manager, Journal of Human Resource and Sustainability Studies 2/2 (2014) 40-58.
[11] C.C. Yang, C.Y.Y. Lin, Does Technical or Strategic HRM Provide a Better Explanation of Organization Performance, Journal of Business 6/2 (2014) 52-62.
[12] B.T. Hazen, J.B. Skipper, J.D. Ezell, C.A. Boone, Big data and predictive analytics for supply chain sustainability: A theory-driven research agenda, Journal of Computers and Industrial Engineering 101 (2016) 592-598.
[13] E.C . Baumann, V.B. Genoulaz, A framework for sustainable performance assessment of supply chain management practices, Journal of Computers and Industrial Engineering 76 (2014) 138-147.
[14] F.R. Lima-Junior, L.C. Ribeiro Carpinetti, Quantitative models for supply chain performance evaluation: A literature review, Journal of Computers and Industrial Engineering 113 (2017) 333-346.
[15] G. Espinosa-Garza, I. Loera-Hernandez, N. Antonyan, Increase of Productivity through the study of work activities in the construction sector, Proceedings of the Manufacturing Engineering Society International Conference, Vigo (Pontevedra), Spain, 2017, 1003-1010.
[16] G. Schuh, M. Riesener, C. Mattern, M. Linnartz, F. Basse, Evaluation collaboration productivity in interdisciplinary product development, Proceedings of the 28th CIRP Design Conference, Nantes, France, 2018, 211-216.
[17] R. Kumar-Singh, H.A. Murty, S.K. Gupta, A.K. Dikshit, An overview of sustainability assessment methodologies, Ecological Indicators 9/2 (2009) 189-212.
[18] A. Moldavska, T. Welo, On the Applicability of Sustainability Assessment Tools in Manufacturing, Proceedings of the 22nd CIRP Conference of Life Cycle Engineering, 2015, 621-626.
[19] Y. Koren, X. Gu, F. Badurdeen, I.S. Jawahir, Sustainable Living Factories for Next Generation Manufacturing, Proceedings of the 15th Global Conference , Sustainable Manufacturing, 2018, 26-36.
[20] L. Cattaneo, L. Fumagalli, M. Macchi, E. Negri, Clarifying Data Analytics Concepts for Industrial Engineering, International Federation of Automatic Control Hosting by Elsevier Ltd, IFAC Papers on Line 51-11 (2018) 820-825.
Uwagi
PL Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-801da609-2374-40e9-858d-0f3e17a66d03
Identyfikatory
DOI 10.5604/01.3001.0012.7972