Overall Performance Evaluation of Tubular Scraper Conveyors Using a TOPSIS-Based Multiattribute Decision-Making Method

Properly evaluating the overall performance of tubular scraper conveyors (TSCs) can increase their overall efficiency and reduce economic investments, but such methods have rarely been studied. This study evaluated the overall performance of TSCs based on the technique for order of preference by similarity to ideal solution (TOPSIS). Three conveyors of the same type produced in the same factory were investigated. Their scraper space, material filling coefficient, and vibration coefficient of the traction components were evaluated. A mathematical model of the multiattribute decision matrix was constructed; a weighted judgment matrix was obtained using the DELPHI method. The linguistic positive-ideal solution (LPIS), the linguistic negative-ideal solution (LNIS), and the distance from each solution to the LPIS and the LNIS, that is, the approximation degrees, were calculated. The optimal solution was determined by ordering the approximation degrees for each solution. The TOPSIS-based results were compared with the measurement results provided by the manufacturer. The ordering result based on the three evaluated parameters was highly consistent with the result provided by the manufacturer. The TOPSIS-based method serves as a suitable evaluation tool for the overall performance of TSCs. It facilitates the optimal deployment of TSCs for industrial purposes

Modeling the interrelationships among barriers to sustainable supply chain management in leather industry

© 2018 Elsevier Ltd The leather industry of Bangladesh is facing considerable amounts of pressure to adopt sustainable supply chain management (SSCM). While there are some studies that have examined barriers to SSCM practices in developed and developing countries in various domains, these are not necessarily applicable to the Bangladeshi leather industry. To bridge this gap, it is crucial to identify most influential barriers to SSCM practices, particularly in the context of developing economies. Therefore, this study identifies such barriers and examines the causal relationships between them with an aim to facilitate the effective implementation of SSCM in the Bangladeshi leather processing industry. Thirty-five barriers to SSCM implementation were identified through a detailed literature review and a survey of leather processing industry experts. Among them, the most common 20 barriers were selected with the help of industry experts. Then, a blended, grey-based Decision Making Trial and Evaluation Laboratory (DEMATEL) approach was utilized to examine their interrelationships. The results demonstrate that nine barriers could be classified as “causal” and eleven as “influenced”. ‘Lack of awareness of local customers in green products’ and ‘lack of commitment from top management’ took high priority in the causal group. ‘Lack of reverse logistics practices’ and ‘Outdated machineries’ were the most influenced barriers. This research uses a leather processing company as a case study for demonstrating the proposed model. The findings aim to support the leather processing industry in a structural way, so that industrial managers can identify the most influential barriers and work to eliminate them. This study may be useful to stakeholders to achieve sustainable development

Fuzzy Set-based Risk Management for Construction Projects

Efficient and comprehensive risk management is critical for successful delivery of engineering, procurement, and construction management (EPCM) projects. Complexity of construction projects is on the rise, which makes it necessary to model uncertainties and to manage risk items related to this class of projects. For decades, researchers and construction practitioners worked together to introduce methods for risk identification and assessment. Considerably less effort was directed towards the development of methods for mitigation, monitoring, and control. The respective individual limitations of these methods prevent the development of comprehensive model which satisfies the needs of practitioners. In this research a comprehensive risk management model “CRMM” is developed to address the limitations of existing methods and to fill the gap between research and practice. The developed model implements a micro system approach to introduce a novel risk identification methodology that provides a systematic procedure to identify risk associated with construction projects. The identification procedure implements root cause analysis and brainstorming technique to identify risk items, consequences, and root causes. The developed CRMM also introduces new method for determination of risk ownership utilizing fuzzy set theory and “One Risk – One Owner” concept. The ownership determination method allocates risk to the owner with highest ability, effectiveness, and capacity to deal with that risk. It also introduces a new qualitative and quantitative evaluation process that utilizes fuzzy set theory and fuzzy probability theory, as well as a new risk mapping procedure which allows for the determination of risk level associated with any project component (e.g., category). The quantitative assessment methodology allows for the use of linguistic and numeric fuzzy evaluations. Fuzzy Linguistic-Numeric Conversion Scheme (FLNCS) is introduced to convert the linguistic evaluations into numeric. The quantitative assessment methodology also introduces the pre-mitigation contingency that represents the contingency fund required for a risk in case no mitigation strategy is implemented. In this respect a novel risk mitigation framework is developed to generate and evaluate possible mitigation strategies for each risk being considered. It also provides a selection procedure which allows users to select the most effective mitigation strategy; making use of fuzzy set theory. The mitigation methodology introduces the post-mitigation contingency that quantifies the contingency required for the selected mitigation strategy. Performance of selected mitigation strategy is monitored using a newly developed risk monitoring method that compares the actually depleted contingency to the post mitigation contingency. The developed monitoring method provides an early warning that alerts users of detected possible failure of selected mitigation strategy. It also determines the correct time for initiation of control process based on a set of qualitative factors. Once risk control process is initiated, the developed control method identifies, evaluates, and selects the most effective control action(s) to support the selected mitigation strategy. In cases where the selected control action fails, the developed control method notifies the user to revise the risk management plan. These notifications allows user to avoid potential failures of similar risk items which are expected to occur in the future. The developed CRMM was coded using VB.Net under Microsoft® windows and .NET framework environment to facilitate its application. A set of case studies are collected from literature and analysed to validate the developed methods within CRMM and to illustrate their essential features. Also, a numerical example elucidates the complete computational processes of the developed comprehensive model