Şebnem Yılmaz Balaman

A Dynamic Maintenance Planning Framework Based on Fuzzy TOPSIS and FMEA: Application in an International Food Company

A maintenance planning framework is developed in this study to reduce and stabilize the maintenance costs of the manufacturing companies. The framework is based on fuzzy technique for order preference by similarity to ideal solution(TOPSIS) and failure mode and effects analysis (FMEA) techniques and supports maintenance planning decisions in a dynamic way. The proposed framework is general and can easily be adapted to a host of manufacturing environments in a variety of sectors. To determine the maintenance priorities of the machines, fuzzy TOPSIS technique is employed. In this regard, ‘risk priority number’ obtained by FMEA and ‘current technology’, ‘substitutability’, ‘capacity utilization’, and ‘contribution to profit’ are used as the criteria. Performance of the resulting maintenance plan is monitored, and maintenance priorities of the machines are updated by the framework. To confirm the viability of the proposed framework, a real-world implementation in an international food company is presented. The results of the application reveal that the proposed maintenance planning framework can effectively and efficiently be used in practice. Copyright

Multiobjective Optimization of Biomass to Energy Supply Chains in an Uncertain Environment

Abstract The aim of this study is to design supply chain network for biomass to energy conversion systems for the regions having high potential of animal wastes and energy crops production and to reveal economical and environmental benefits from these systems. To this aim, a fuzzy multiobjective mixed integer linear programming (MILP) model is constructed. The model includes environmental and monetary objectives and it is structured as a multiperiod model in order to consider variation in the parameters. The model is solved by using different fuzzy goal programming (FGP) approaches.

Biomass to Energy Supply Chain Network Design: An Overview of Models, Solution Approaches and Applications

Energy production from biomass is an alternative and additive way to fossil fuel based energy production to reduce the dependency on limited fossil fuel sources and mitigate the harmful environmental impacts of these systems. One of the major challenges in establishing efficient renewable energy systems is the complex supply chain structure in an uncertain decision environment, various decisions to be made and different conflicting criteria/objectives. This study describes the key issues in decision making for biomass to energy supply chains such as decision levels, uncertainty and sustainability concepts. It also provides a comprehensive review and systematic classification of the current literature on decision making approaches for design, management and operation of biomass to energy supply chains. This study allows readers to identify the decision making methods that satisfy the problem specific requirements and offer a clear vision of the advances in the field.

A Novel Approach to Local Level Design of Bioenergy Supply Chains Integrated with District Heating Systems

This study aims to develop a comprehensive decision support system (DSS) for design and management of local bioenergy supply chains by tackling inherent uncertainties. To this aim, a fuzzy programming-based multiobjective mixed integer linear programming (MILP) model is constructed. To explore the viability of the proposed DSS, computational experiments are performed on a real-world problem, and further analyses are conducted. The results reveal that the proposed model can effectively be used in practice.