Multi-criteria decision making approach to production line optimization

Abstract The problem of optimization assembly lines for rarely repeatable products with low volumes will be addressed in this paper. In this kind of production each product should be treated as a project with different cycle time on each station. Balance of assembly lines processing separate projects is impacted by uncertainty, assembly methods are not fully automated. Daily operations in this kind of activity needed an effective and fast method to support decision making by assembly line managers and production planners. For this purpose Analytical Hierarchy Method (AHP) and TOPSIS methods are used. The empirical study presents four possible optimization configurations for comparison and evaluation using the AHP and TOPSIS methods.

[1]  Wojciech Sałabun,et al.  A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management , 2020, Energies.

[2]  Daniel E. Hastings,et al.  3.4.1 A Framework for Understanding Uncertainty and its Mitigation and Exploitation in Complex Systems , 2005 .

[3]  Agnieszka Konys,et al.  Approach to Practical Ontology Design for Supporting COTS Component Selection Processes , 2013, ACIIDS.

[4]  Thomas L. Saaty What is the analytic hierarchy process , 1988 .

[5]  Bernard Roy,et al.  Multi-criteria assignment problem with incompatibility and capacity constraints , 2006, Ann. Oper. Res..

[6]  S. M. Hatefi,et al.  A common weight MCDA–DEA approach to construct composite indicators , 2010 .

[7]  Roman Słowiński,et al.  Questions guiding the choice of a multicriteria decision aiding method , 2013 .

[8]  Katarzyna Szopik-Depczyńska,et al.  User-Driven Innovation in Poland: Determinants and Recommendations , 2019, Sustainability.

[9]  Wojciech Sałabun,et al.  Multicriteria Approach to Sustainable Transport Evaluation under Incomplete Knowledge: Electric Bikes Case Study , 2019, Sustainability.

[10]  Konys,et al.  Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base , 2019, Sustainability.

[11]  Alexandre Dolgui,et al.  A taxonomy of line balancing problems and their solutionapproaches , 2013 .

[12]  Tabasam Rashid,et al.  A New Method to Support Decision-Making in an Uncertain Environment Based on Normalized Interval-Valued Triangular Fuzzy Numbers and COMET Technique , 2020, Symmetry.

[13]  Dr.-Ing. Arno Kühn,et al.  A practical Framework for the Optimization of Production Management Processes , 2019 .

[14]  Jarosław Wątróbski,et al.  Generalised framework for multi-criteria method selection: Rule set database and exemplary decision support system implementation blueprints , 2018, Data in brief.

[15]  Reza Baradaran Kazemzadeh,et al.  PROMETHEE: A comprehensive literature review on methodologies and applications , 2010, Eur. J. Oper. Res..

[16]  Carlos Henggeler Antunes,et al.  Multi-Objective Optimization and Multi-Criteria Analysis Models and Methods for Problems in the Energy Sector , 2016 .

[17]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[18]  A. Lotfi,et al.  Fuzzy goal programming to optimization the multi-objective problem , 2014 .

[19]  Agnieszka Konys,et al.  Knowledge systematization for ontology learning methods , 2018, KES.

[20]  G. Ioppolo,et al.  Innovation level and local development of EU regions. A new assessment approach , 2020 .