A Knowledge Enriched Computational Model to Support Lifecycle Activities of Computational Models in Smart Manufacturing

Due to the needs in supporting lifecycle activities of computational models in Smart Manufacturing (SM), a Knowledge Enriched Computational Model (KECM) is proposed in this dissertation to capture and integrate domain knowledge with standardized computational models. The KECM captures domain knowledge into information model(s), physics-based model(s), and rationales. To support model development in a distributed environment, the KECM can be used as the medium for formal information sharing between model developers. A case study has been developed to demonstrate the utilization of the KECM in supporting the construction of a Bayesian Network model. To support the deployment of computational models in SM systems, the KECM can be used for data integration between computational models and SM systems. A case study has been developed to show the deployment of a Constraint Programming optimization model into a Business To Manufacturing Markup Language (B2MML) -based system. In another situation where multiple computational models need to be deployed, the KECM can be used to support the combination of computational models. A case study has been developed to show the combination of an Agent-based model and a Decision Tree model using the KECM. To support model retrieval, a semantics-based method is suggested in this dissertation. As an example, a dispatching rule model retrieval problem has been addressed with a semantics-based approach. The semantics-based approach has been verified and it demonstrates good capability in using the KECM to retrieve computational models

An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM

A Decision Tool for Supplier Selection That Takes into Account Power and Performance

Companies select their suppliers to provide required performance while being successful partners. An important aspect of collaboration is the power relationship between the company and its suppliers. Although the significance of power in supplier selection is acknowledged, published work rarely includes assessment of power. An empirical study on selecting suppliers for new product developments in a major European diesel engine manufacturing company, supported by three smaller studies with electronic engineering companies, frames overall questions regarding the importance of incorporating power into supplier selection and how this might be achieved. This research proposes an approach that assesses both performance and power and integrates the assessment results by modelling the relative effects of power and performance. It positions the suppliers into six scenarios (ideal, satisfying, tolerable, unfavourable, risky and tough) which depict to what extent a supplier is ‘suitable’ to work with. A reverse analysis reviews the relationship when several suppliers appear suitable. An assessment method is developed incorporating both subjective and objective data for qualitative and quantitative criteria. It combines two decision making methods, AHP and TOPSIS, with triangular fuzzy numbers. Multiple judgements from several decision makers are synthesised. This method is adapted for performance assessment of single, group and cross-group suppliers. Weights are calculated for the criteria, and combined with calculations of supplier performance against each criterion to provide an overall assessment and supplier profile. Power is quantified against a set of power determinants and power relations (supplier dominance, buyer dominance and balanced) are determined. The effects of supplier perceptions (objective, optimistic and pessimistic) are estimated in the calculation. The proposed approach involves complex calculations and a prototype software tool is developed with graphical interfaces. The tool includes performance criteria and power determinants collected from literature and allows users to define new ones. Application to an agriculture case enables the sustainable performance of suppliers (farmers) to be evaluated and compared

Journal of Telecommunications and Information Technology, 2006, nr 4

kwartalni

Diseño de una metaheurística GRASP para el problema de la programación de la producción en una empresa del sector cerámico bajo un entorno Distributed Permutation Flow Shop with Flowline Elegibility, que minimice la tardanza total teniendo en cuenta la importancia del producto y del cliente

Este proyecto de investigación tiene como objetivo resolver el problema de programación de la producción en una industria del sector cerámico cuyo objetivo es la minimización de la tardanza total. Este problema tiene lugar en una empresa líder en revestimientos de pisos y paredes, donde la tardanza total hace referencia al tiempo de retraso total de un trabajo entregado después de las fechas negociadas con los clientes. En la actualidad, la compañía presenta altos niveles de incumplimiento con respecto a la fecha de entrega de los pedidos de fabricación, lo que se refleja en 935 días de retraso total durante el primer trimestre del año. Este retraso se puede mejorar a través de diferentes técnicas de ingeniería para la programación de la producción, creando así una mejor solución como se evidencia en estudios científicos anteriores. El sistema estudiado es un Distributed Permutation Flow Shop with Flowline Elegibility (DPFSFE) que considera la importancia de los productos y los clientes. Para resolver el problema, se propone un modelo de programación lineal entera mixta en una primera etapa. Posteriormente, debido a que se considera un problema NP-Hard, se diseñó e implementó una metaheurística GRASP hibridizada con las metodologías PAES y AHP. Para evaluar el impacto de la técnica propuesta, los resultados se compararon con los obtenidos con la implementación de la regla de despacho Apparent Tardiness Cost with Setups (ATCS). La metaheurística propuesta mejora la programación real de la compañía en un 67% y es un 76% mejor en comparación con la regla ATCS, en términos de tardanza total.This research project aims to solve the scheduling problem in an industry of the ceramic sector which objective is the minimization of total tardiness. This problem takes place in a leading floor and wall covering company, where the total tardiness refers to the total delay time of a job delivered after the dates negotiated with customers. At present, the company presents high non-compliance levels with respect to the date of delivery of manufacturing orders , reflected in 935 days of total tardiness during the first quarter of the year. This delay can be improved through different engineering techniques for production scheduling, thus creating a better solution as evidenced in previous scientific studies.The system studied is a Distributed Permutation Flow Shop with Flowline Elegibility (DPFSFE) that considers products and customers importance. To solve the problem a mixed integer linear programming model is proposed in a first stage. Later, due to the NP- hardness of the problem, with a GRASP metaheuristic hybridized with PAES and AHP methodologies was designed and implemented. In order to evaluate the impact of the proposed technique, the results were compared with those obtained with the implementation of the dispatching rule Apparent Tardiness Cost with Setups (ATCS). The proposed metaheuristic improves the actual scheduling of the company in a 67% and is a 76% better in comparison with ATCS rule, in terms of total tardiness.Ingeniero (a) IndustrialPregrad