Analyzing Process Quality Control Variables Using Fuzzy Cognitive Maps

IF 0.9 Q4 ENGINEERING, INDUSTRIAL

Management and Production Engineering Review Pub Date : 2023-07-20 DOI:10.24425/mper.2022.142386

J. Cogollo, Orfani VALENCIA-MENA

引用次数: 0

Abstract

Meeting quality characteristics of products and processes is an important issue for customer satisfaction and business competitiveness. It is necessary to integrate new techniques and tools that improve and complement traditional process variables analysis. This paper proposes a new methodological approach to analyze process quality control variables using Fuzzy Cognitive Maps. Application of the methodology in the production process of carbonated beverages allowed identifying process variables with the greatest inﬂuence on ﬁnished product quality. The process variables with the greatest impact on carbon dioxide content in the beverage were the beverage temperature in the ﬁller, the carbo-cooler pressure, and the ﬁller pressure.

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用模糊认知图分析过程质量控制变量

满足产品和工艺的质量特征是关系到客户满意度和企业竞争力的重要问题。有必要集成新的技术和工具，以改进和补充传统的过程变量分析。本文提出了一种利用模糊认知映射分析过程质量控制变量的新方法。将该方法应用于碳酸饮料的生产过程中，可以确定对成品质量影响最大的过程变量。对饮料中二氧化碳含量影响最大的工艺变量是灌装机中的饮料温度、碳冷却器压力和灌装机压力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Management and Production Engineering Review ENGINEERING, INDUSTRIAL-

CiteScore

2.80

自引率

21.40%

发文量

期刊介绍： Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.