Development of new evaluation methods for qualitative alternatives, using fuzzy calculations

Evaluation, selection and finally decision making are all among important issues, which engineers face in long run of projects. Engineers implement mathematical and nonmathematical methods to make accurate and correct decisions, whenever needed. As extensive as these methods are, effects of any selected method on outputs achieved and decisions made are still suspicious. This is more controversial and challengeable, where evaluation is made among non-quantitative alternatives. In civil engineering and construction management problems, criteria include both quantitative and qualitative ones, such as aesthetic, construction duration, building and operation costs, and environmental considerations. As the result, decision making frequently takes place among non-quantitative alternatives. It should be noted that traditional comparison methods, including clear-cut and inflexible mathematics, have always been criticized. This paper demonstrates a brief review of traditional methods of evaluating alternatives. It also offers a new decision making method using, fuzzy calculations. The main focus of this research is some engineering issues, which have flexible nature and vague borders. Suggested method provides analyzability of evaluation for decision makers. It is also capable to overcome multi criteria and multi-referees problems. In order to ease calculations, a program named DeMA is introduced.

Triangular Linguistic Fuzzy based performance measurement model for supply chain to assess leanness attributes

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Selection method for sustainable building

For a sustainable building industry, not only should the environmental and economic indicators be evaluated but also the societal indicators for building. Current indicators can be in conflict with each other, thus decision making is difficult to clearly quantify and assess sustainability. For the sustainable building, the objectives of decreasing both adverse environmental impact and cost are in conflict. In addition, even though both objectives may be satisfied, building management systems may present other problems such as convenience of occupants, flexibility of building, or technical maintenance, which are difficult to quantify as exact assessment data. These conflicting problems confronting building managers or planners render building management more difficult. This paper presents a methodology to evaluate a sustainable building considering socio-economic and environmental characteristics of buildings, and is intended to assist the decision making for building planners or practitioners. The suggested methodology employs three main concepts: linguistic variables, fuzzy numbers, and an analytic hierarchy process. The linguistic variables are used to represent the degree of appropriateness of qualitative indicators, which are vague or uncertain. These linguistic variables are then translated into fuzzy numbers to reflect their uncertainties and aggregated into the final fuzzy decision value using a hierarchical structure. Through a case study, the suggested methodology is applied to the evaluation of a building. The result demonstrates that the suggested approach can be a useful tool for evaluating a building for sustainability.

A study on matching and multi-objective fuzzy control strategy of heavy truck suspension system

Matching method of heavy truck-rear air suspensions is discussed, and a fuzzy control strategy which improves both ride comfort and road friendliness of truck by adjusting damping coefficients of the suspension system is found. In the first place, a Dongfeng EQ1141G7DJ heavy truck’s ten DOF whole vehicle-road model was set up based on Matlab/Simulink and vehicle dynamics. Then appropriate passive air suspensions were chosen to replace the original rear leaf springs of the truck according to truck-suspension matching criterions, consequently, the stiffness of front leaf springs were adjusted too. Then the semi-active fuzzy controllers were designed for further enhancement of the truck’s ride comfort and the road friendliness. After the application of semi-active fuzzy control strategy through simulation, is was indicated that both ride comfort and road friendliness could be enhanced effectively under various road conditions. The strategy proposed may provide theory basis for design and development of truck suspension system in China.