Interpretive Structural Model of Key Performance Indicators for Sustainable Manufacturing Evaluation in Cement Industry

This paper aims to analyze the relationships among the Key Performance Indicators (KPIs) for sustainable manufacturing evaluation in the cement industry. The initial KPIs have been identified and derived from literature, and then validated by industry survey. As a result, three factors dividing into a total of thirteen indicators have been proposed as the KPIs for sustainable manufacturing evaluation in cement industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs. The results show the indicators of economic factor are regarded as the basic indicator, while the indicators of environmental factor are indicated to be the leading indicator. Of those indicators, raw material substitution is regarded as the most influencing indicator. The ISM model can aid the cement companies by providing a better insight in evaluating sustainable manufacturing performance

Interpretive Structural Model of Key Performance Indicators for Sustainable Manufacturing Evaluation in Cement Industry

This paper aims to analyze the relationships among the Key Performance Indicators (KPIs) for sustainable manufacturing evaluation in the cement industry. The initial KPIs have been identified and derived from literature, and then validated by industry survey. As a result, three factors dividing into a total of thirteen indicators have been proposed as the KPIs for sustainable manufacturing evaluation in cement industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs. The results show the indicators of economic factor are regarded as the basic indicator, while the indicators of environmental factor are indicated to be the leading indicator. Of those indicators, raw material substitution is regarded as the most influencing indicator. The ISM model can aid the cement companies by providing a better insight in evaluating sustainable manufacturing performance

Dual resource constrained em sistemas de produção industrial: estudo de simulação

Os sistemas de produção industrial são limitados por diversas categorias de recursos: pessoas, máquinas, ferramentas, sistemas de transporte, entre outras. Na terminologia anglosaxónica é comum usar o termo Dual Resource Constrained (DRC), para designar sistemas limitados pela disponibilidade destes tipos de recursos, usualmente pessoas e máquinas. O desempenho de sistemas do tipo DRC é determinado por diversos fatores, nomeadamente pela forma de como os recursos humanos (trabalhadores) são alocados às máquinas (i.e., regras de alocação dos trabalhadores) e pela sequência pela qual os trabalhos são processados nessas máquinas (i.e., regras de despacho). Este trabalho utiliza um ambiente produtivo virtual, com recurso ao software de simulação discreta Arena, para avaliar um conjunto de regras de alocação de trabalhadores e de regras de despacho na operação de sistemas DRC. No estudo são considerados vários cenários experimentais, analisando o impacto destas regras em diferentes configurações dos sistemas de produção. De uma forma geral, os resultados obtidos permitiram concluir que as regras testadas para alocação dos trabalhadores às máquinas têm um forte impacto na performance do sistemas produção testados, nomeadamente no que se refere à definição para onde os trabalhadores se devem deslocar (where rules). O estudo procura ainda apontar possíveis caminhos de trabalho futuro para a melhoria do desempenho deste tipo de sistemas de produção.Industrial production systems are usually constrained by two major resource categories: workers, machines, tools, transportation systems and others. In the Anglo-Saxon terminology, it is usual to use the term Dual Resource Constrained (DRC), to define systems constrained by machines and workers. Their performance is determined by numerous causes: How the workers are allocated to the machines and the order in which the jobs should be processed are some examples. This project uses a virtual production environment, by accessing a discrete simulation software called Arena. It is used to evaluate a set of rules that determine the way workers should move and the order of the jobs being processed in a DRC system. In this paper, are several different scenarios with several rules being analyzed. The results of this project allowed to conclude that between the several tested rules, the ones that command the way workers should move (where rules) had a major impact in the system's performances. This study also tried to point possible future ways to improve the performance of these kinds of systems