Mahdi Sabaghi

Sustainability assessment using fuzzy-inference technique (SAFT)

A fuzzy-inference method was introduced to evaluate product/process sustainability.The proposed methodology does not require generation of rules.A comparison with fuzzy rule-base technique was done.Results were satisfactory and indicated the applicability of the proposed technique. Green products are increasingly becoming the center of attention for policy and decision makers worldwide not only because of environmental and eco-systems crisis but also to satisfy the current competitiveness in the markets. With this aim, it is highly attractive to count with mathematical tools that allow assessing the sustainability of the products. In this regard, fuzzy techniques have been broadly used in different studies due to uncertainty and vagueness associated with sustainability problems. However, these studies are mostly based on fuzzy rules generation which is time consuming and also can lead to redundancy and inaccuracy. In this study, we introduced a fuzzy-inference system to evaluate product/process sustainability (SAFT). The proposed method does not require generation of rules which simplifies the procedure and makes it more precise. Furthermore, fuzzy analytic hierarchy process accompanied by Shannons entropy formula was employed to determine the relative importance of each element in the hierarchy. The methodology SAFT was compared with fuzzy rule-base technique and impressively pretty the same results were obtained. The method introduced in this paper was built as a user interface platform which can be used as a fuzzy expert system to facilitate the sustainability assessment of products/processes in different manufacturing industries.

Hybrid GA for material routing optimization in supply chain

This research proposes a mathematical model for supply, production and distribution.For solving the model, it proposed e new methodology based on GA, FAHP and TOPSIS.The result of model shows that it is robust.It can also be applied to other industrial environments with slight modifications. In designing a supply chain (SC) system, the problem arises when a company has unsatisfactory inventory control policy and material routing between supplier-producer and distributor in SC considering specified cost and demand. The integration of decisions of different functions into a single optimization model is the base of this research. The aim of this paper is to study and compare the existing models of supply, production and distribution in SC and propose a model which integrates mentioned criteria in supply chain management (SCM). Furthermore, it proposes a new method for calculation of fitness function in genetic algorithm (GA) process. The successful designing of this model has led us to explore the use of heuristic methods such as GA to quantify the flow of SC, information and material flow. At first, fuzzy analytic hierarchy process (FAHP) is adapted to evaluate objective function weights in SC. Then final weights of objective function are determined by the technique for order of preference by similarity to ideal solution (TOPSIS). This research also simulated the real company SC operations, and determines the most effective strategic and operational policies for an effective SC system. The result obtained from the model shows that it is robust. This model can also be applied to other industrial environments with slight modifications.

Kanban and value stream mapping analysis in lean manufacturing philosophy via simulation: a plastic fabrication (case study)

This article is a practical study focusing on three lean manufacturing techniques, which are Kanban production system, setup time reduction, and total productive maintenance (TPM) in a plastic fabrication industry. Nevertheless the methodology can be simply expanded to other industries as well. Kanban is implemented as the main subject for just–in–time (JIT) production systems, while value stream mapping (VSM) is utilised to focus more on the streams in the production processes. The three main causes for work–in–process (WIP) are selected based on the cause and effect diagram in the company. Based on simulation and the results obtained from ANOVA, Kanban and TPM are recognised as the two most significant techniques in comparison with the setup time reduction technique which has the least significance. Furthermore, the study signifies that the Kanban–TPM system widely stimulates the reduction in both lead time and WIP inventory. Finally, the new VSM of the company signifies the alleviation of information exchange and paper works between various departments engaged in the process in comparison to the prior situation.

Evaluation of Cost-Effectiveness Criteria in Supply Chain Management: Case Study

The aim of this paper is to evaluate and prioritize the proposed cost-effectiveness criteria in supply chain management using fuzzy multiple attribute decision-making (MADM) approach. Over the past few years, the determination of suitable cost-effectiveness criteria in the supply chain has become a key strategic issue. However, the nature of these kinds of decisions is usually complex and unstructured. Many quantitative and qualitative factors must be considered to determine the suitable criteria. As the human decision-making process usually contains fuzziness and vagueness, a hierarchy of MADM model based on fuzzy-sets theory is used in this research. Using a fuzzy analytic hierarchy process (FAHP), the weights of criteria and subcriteria are determined and then the final ranking is determined by technique for order preference by similarity to ideal solution (TOPSIS). Finally, fuzzy TOPSIS (FTOPSIS) is employed to compare the results with classic TOPSIS. This paper concludes that the subcriteria in all the items are in the same rank.