Title: Decision support system for production improvement in a cork flooring company

Authors: Luís Rodrigues; Luís Pinto Ferreira; Francisco J.G. Silva; José Carlos Sá

Addresses: ISEP – School of Engineering, Polytechnic of Porto, R. Dr. Antº Bernardino de Almeida, 431, 4200-072, Porto, Portugal ' ISEP – School of Engineering, Polytechnic of Porto, R. Dr. Antº Bernardino de Almeida, 431, 4200-072, Porto, Portugal; INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal ' ISEP – School of Engineering, Polytechnic of Porto, R. Dr. Antº Bernardino de Almeida, 431, 4200-072, Porto, Portugal; INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal ' ISEP – School of Engineering, Polytechnic of Porto, R. Dr. Antº Bernardino de Almeida, 431, 4200-072, Porto, Portugal; INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal

Abstract: Information is a company's key factor for optimal activity efficiency. Gathering and processing data for decision making provides optimal solutions in production, quality control, distribution, sales, etc. resulting in reduced waste costs regarding materials, time, consumables, repairs, etc. This research demonstrates the importance of decision support systems (DSS) and simulation tools in process optimisation, focusing on the industrial sector and Industry 4.0 concept. Consequently, a DSS, named ARSimTool, was developed in a cork processing company, to perform the simulation of occupational levels of its production lines. This was requested as an alternative to the existing method, offering advanced representation capabilities of the real model and additional functionality on interface accessibility, autonomous data recovering, creation of testing scenarios, management of the workflow along the production floor, among others.

Keywords: decision support system; DSS; lean manufacturing; agile manufacturing; strategic manufacturing; smart manufacturing; Industry 4.0; production improvement; simulation; productivity; capacity usage efficiency; production planning.

DOI: 10.1504/WRSTSD.2023.133887

World Review of Science, Technology and Sustainable Development, 2023 Vol.19 No.4, pp.349 - 364

Received: 26 Dec 2020
Accepted: 05 Jul 2021
Published online: 05 Oct 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article