Performance Evaluation for the Sustainable Supply Chain Management

Supply chain SC activities transform natural resources, raw materials, and components into various finished products that are delivered to end customers. A high efficient SC would bring great benefits to an enterprise such as integrated resources, reduced logistics costs, improved logistics efficiency, and high quality of overall level of services. In contrast, an inefficient SC will bring additional transaction costs, information management costs, and resource waste, reduce the production capacity of all enterprises on the chain, and unsatisfactory customer relationships. So the evaluation of a SC is important for an enterprise to survive in a competitive market in a globalized business environment. Therefore, it is important to research the various methods, performance indicator systems, and technology for evaluating, monitoring, predicting, and optimizing the performance of a SC. A typical procedure of the performance evaluation (PE) of a SC is to use the established evaluation performance indicators, employ an analytical method, follow a given procedure, to carry out quantitatively or qualitatively comparative analysis to provide the objective and accurate evaluation of a SC performance in a selected operation period. Various research works have been carried out in proposing the performance indicator systems and methods for SC performance evaluations. But there are no widely accepted indicator systems that can be applied in practical SC performance evaluations due to the fact that the indicators in different systems have been defined without a common understanding of the meanings and the relationships between them, and they are nonlinear and very complicated

Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems

This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book

SCS: 60 years and counting! A time to reflect on the Society's scholarly contribution to M&S from the turn of the millennium.

The Society for Modeling and Simulation International (SCS) is celebrating its 60th anniversary this year. Since its inception, the Society has widely disseminated the advancements in the field of modeling and simulation (M&S) through its peer-reviewed journals. In this paper we profile research that has been published in the journal SIMULATION: Transactions of the Society for Modeling and Simulation International from the turn of the millennium to 2010; the objective is to acknowledge the contribution of the authors and their seminal research papers, their respective universities/departments and the geographical diversity of the authors' affiliations. Yet another objective is to contribute towards the understanding of the overall evolution of the discipline of M&S; this is achieved through the classification of M&S techniques and its frequency of use, analysis of the sectors that have seen the predomination application of M&S and the context of its application. It is expected that this paper will lead to further appreciation of the contribution of the Society in influencing the growth of M&S as a discipline and, indeed, in steering its future direction

A DESIGN METHODOLOGY FOR REMANUFACTURING AND REMANUFACTURABILITY ASSESSMENT

Ph.DDOCTOR OF PHILOSOPH

Developement of a job rotation algorithm to reduce occupational exposure in the automotive industry

Musculoskeletal disorders remain the most reported occupational health workplace problem, affecting workers in all sectors of economic activity. The automotive industry is one of the industries with the highest prevalence of musculoskeletal symptoms, mainly due to the biomechanical risk factors that workers are exposed to during their workday. As this industry is one of the largest industrial forces that has contributed significantly to the growth of the global economy, it is crucial to develop efficient solutions that can be implemented in workplaces to improve working conditions by eliminating or reducing workers' exposure to the main biomechanical risk factors. The present dissertation attempts to understand the short-term relationships between biomechanical risk factors and musculoskeletal symptoms in the automotive assembly line, in addition to providing an organizational strategy that uses a mathematical approach to mitigate exposure to the same risk factors and reduce the prevalence/incidence of musculoskeletal disorders. Therefore, this dissertation presents three main investigations. The first study with a cohort design determines the short-term associations between biomechanical risk factors and musculoskeletal symptoms in the upper limbs and low back in an automotive plant. The workers were divided into low and high-risk groups for various risk factors. The results suggested that workers who were in the high-risk group had a higher likelihood to report adverse effects on their musculoskeletal symptoms at the end of a work week, particularly when exposed to certain risk factors, such as: posture for symptoms in the neck, right wrist, and left shoulder. The second study proposes a mathematical formulation based on a genetic algorithm that considers the assessment of biomechanical risk factors (EAWS) in the workplace, workers’ qualifications, and organizational aspects inherent in the operation of the production line. The algorithm is based on three criteria: enhancing diversity, ensuring team homogeneity, and reducing exposure to biomechanical risk factors. The success of the algorithm in meeting these criteria has been verified. In addition, when comparing the results of the algorithm with the results of manual job rotation plans (created by a team leader), it was shown that the mathematical solution was more efficient, not only in relation to the three criteria, but also in terms of time spent on this task. Finally, the third study complements the second by comparing the results obtained via the genetic algorithm with the data obtained through the rotation plans made by team leaders of several teams on the assembly lines. Therefore, the aim of this study was to XIX evaluate the effectiveness of the algorithm in creating job rotation plans compared to the manual process of team leaders in terms of diversity, homogeneity, exposure, shift working sequence quality and matrix quality. The job rotation plans of 7 teams (89 workers) from the assembly area were included in the sample. Exposure was the only criterion that did not show significant differences between the two methods, however, all variables at the individual level showed high values in the limits of agreement. The values of diversity, homogeneity, shift working sequence quality, and matrix quality of the job rotation plan generated by the genetic algorithm were on average higher than the values of the team leaders’ job rotation plan. These results show that implementing the genetic algorithm has a promising potential to create job rotation plans that reduce musculoskeletal disorders in the automotive industry and as well as to reduce the time associated with the team leader completing this task.As lesões músculo-esqueléticas continuam a ser o principal problema de saúde reportado no local de trabalho, afetando trabalhadores em todos os setores de atividades. A indústria automóvel é um dos setores com maior prevalência de sintomatologia músculo-esquelética, principalmente devido aos fatores de risco biomecânicos a que os trabalhadores estão expostos durante o seu dia de trabalho. Sendo esta indústria uma das maiores forças industriais, que contribuí de forma significativa para o crescimento da economia global e nacional, é fulcral desenvolver soluções eficientes para implementar nos postos de trabalho por forma a melhorar as suas condições, eliminando ou reduzindo a exposição dos trabalhadores aos principais fatores de risco biomecânicos. A presente dissertação procura compreender os efeitos a curto prazo dos fatores de risco biomecânicos sobre a sintomatologia músculo-esquelética na linha de montagem de uma indústria automóvel, e providencia uma estratégia organizacional, recorrendo a uma abordagem matemática, para mitigar a exposição a condições de trabalho adversas e reduzir a incidência de lesões e sintomatologia músculo-esqueléticas. Para a concretização desta dissertação, foram desenvolvidos três estudos. O primeiro estudo, com um desenho prospetivo e uma amostra de 228 trabalhadores, determinou as associações a curto prazo entre os fatores de risco biomecânicos e a sintomatologia músculo-esquelética nos membros superiores e na região lombar numa fábrica da indústria automóvel. Os trabalhadores foram divididos em grupos de baixo e elevado risco para os diferentes fatores de risco. Os resultados sugerem que ao final de uma semana de trabalho, os trabalhadores que pertencem ao grupo de alto risco têm uma predisposição superior para reportarem efeitos desfavoráveis na sua sintomatologia músculo-esquelética, principalmente quando sujeitos a determinados fatores de risco, como é o caso da postura para a sintomatologia no pescoço, punho direito e ombro esquerdo. O segundo estudo propõe uma formulação matemática com base num algoritmo genético, que tem em conta a avaliação dos fatores biomecânicos presentes nos postos de trabalho (EAWS), a qualificação dos trabalhadores e aspetos organizacionais inerentes ao funcionamento da linha de produção. O algoritmo baseia-se em três critérios: melhorar a diversidade da exposição aos fatores de risco, garantir a homogeneidade da equipa e reduzir a exposição aos fatores de risco biomecânicos. O sucesso do algoritmo no cumprimento destes critérios foi verificado. Adicionalmente, quando se compararam os resultados do algoritmo com os resultados dos XXI planos de rotação criados manualmente por um team leader, verificou-se que a solução matemática despendia menos tempo na concretização da tarefa. Por fim, o terceiro estudo complementa o segundo comparando os resultados obtidos pelo algoritmo genético e os dados obtidos pelos planos de rotação gerados pelos team leaders de várias equipas da linha de montagem. Assim, o objetivo deste estudo é avaliar a eficácia do algoritmo em gerar planos de rotação, quando comparado com o processo manual realizado pelos team leaders quanto à diversidade, homogeneidade, exposição, sequência de estações de trabalho e qualidade da matriz. Os planos de rotação de 7 equipas (89 trabalhadores) da área da montagem foram incluídos na amostra. A análise de grupo demonstrou que a exposição é o único critério que não apresenta diferenças significativas entres os dois métodos, no entanto, a nível individual todas as variáveis apresentaram valores elevados nos limites de concordância. Os valores de diversidade, homogeneidade, sequência de postos de trabalho e qualidade da matriz do plano de rotação gerado pelo algoritmo genético são, em média, superiores quando comparados com os valores do plano de rotação do team leader. Estes resultados revelam um potencial promissor na implementação do algoritmo genético para a criação de planos de rotação para diminuir o tempo associado à realização desta tarefa pelo team leader, mas também no seu papel ativo na redução das lesões músculo-esqueléticas na indústria automóvel