Use of Mathematical Models in a Mechanical Metal Industry to Improve Production Planning and Control

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Author(s): Leoni Pentiado Godoy (University Federal de Santa Maria, Brazil), Wagner Pietrobelli Bueno (Universidade Federal do Rio Grande, Brazil), Tais Pentiado Godoy (Universidade Federal de Santa Maria, Brazil), Clandia Gomes (Universidade Federal de Santa Maria, Brazil), Maria Carolina Martins Rodrigues (Algarve University, Portugal)and Luciana Aparecida Barbieri da Rosa (Universidade Federal de Santa Maria, Brazil)
Copyright: 2021
Pages: 19
Source title: Advanced Models and Tools for Effective Decision Making Under Uncertainty and Risk Contexts
Source Author(s)/Editor(s): Vicente González-Prida (University of Seville, Spain & National University of Distance Education, Spain)and María Carmen Carnero (University of Castilla-La Mancha, Spain)
DOI: 10.4018/978-1-7998-3246-1.ch013

Keywords: Business & Management / Business and Organizational Research / Business Science Reference / Risk Management & Analysis

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Abstract

This chapter aims to propose an improvement in decision making in the planning sector and production control (PPC) with application of a mathematical model. In the methodology, the qualitative approach was used because the linguistic codifications are interpreted and characterized by a case study applying a questionnaire to the managers of the company of the metal mechanic sector. In this context, six constructs were structured as a proposal for performance improvement, being composed of costs, management, inspection, processes, and capacity. The chapter reports the main results achieved during fuzzy sets application, obtaining a better result compared to FAHP in which there were certain oscillations between the percentage of constructs. The construct prioritized by managers and specialists was the cost construct, reaching 38.60%, being advantageous for the industry when the cost is placed in order of manufacture (subconstruct), followed by the prioritized management construct with 28.50%.

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Use of Mathematical Models in a Mechanical Metal Industry to Improve Production Planning and Control

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