Using FANP approach on selection of competitive priorities based on cleaner production implementation: a case study in PCB manufacturer,Taiwan

The aim of this paper is to identify and discuss some of the important and critical decision criteria including cleaner production implementation of an efficient system to prioritize competitive priorities. Fuzzy analytic network process (FANP) based methodology is discussed to tackle the different decision criteria involved in the selection of competitive priorities in current business scenario. FANP is an efficient tool to handle the fuzziness of the data involved in deciding the preferences of different decision variables. The linguistic level of comparisons produced by the professionals and experts for each comparison are tapped in the form of triangular fuzzy numbers to construct fuzzy pairwise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy which contains different criteria, attributes and alternatives at wider perspective. The proposed model can provide a hierarchical framework for the cleaner production implemented organization to select on its competitive priorities.     

Tool selection for optimal part production: a Lagrangian relaxation approach

This paper extends previous work on implementation problems associated with a flexible system that produces flat sheet-metal parts with interior holes. The paper makes four main contributions. First, we formulate the problem of selecting tooling and design standards to minimize the cost of producing parts as an optimization model. Second, we develop a projected subgradient algorithm for the Lagrangian relaxation of the problem by using the model's special structure to develop relationships between the Lagrangian multipliers. Third, we demonstrate that the algorithm produces close to optimal solutions (duality gap less than 2%) very quickly on a number of problems derived using a substantial data set obtained from a Chicago area firm. Fourth, an important variant of the traditional repair kit problem is shown to be a special case of the tool selection problem.     

An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information

Nowadays selecting the most suitable robot is a difficult task for manufacturing firms due to increase in production demands and availability of various robot models. Robot evaluation and selection can be regarded as a multiple criteria decision-making (MCDM) problem and three key issues are the assessment of robots, the determination of criteria weights and the prioritisation of alternatives. This paper aims to propose an integrated model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX approach for handling robot selection problems with incomplete weight information. The new model can not only manage uncertain and imprecise assessment information of decision-makers with the aid of hesitant 2-tuple linguistic term sets, but also derive the important weights of criteria objectively when the weight information is incompletely known. Moreover, based on the extended QUALIFLEX algorithm, the priority orders of robots can be clearly determined and a more reasonable and credible solution can be yielded in a particular industrial application. Finally, a robot selection case study is carried out, and comparative experiments indicate the practicality and effectiveness of the proposed integrated linguistic MCDM approach.     

Integrating resource criticality assessment into evaluation of cleaner production possibilities for increasing resource efficiency

A stable and secure source of raw materials is the key to any successful industrial activity. Resource criticality is often discussed in the context of the impact on the economies of certain geographic regions. However, the availability of required resources first of all concerns the competitiveness of industrial companies, especially in those countries which do not possess abundant natural resources. The Lithuanian economy relies heavily on imports since the country does not have abundant natural resources. The paper introduces resource criticality as an additional dimension for evaluating and prioritizing resource efficiency improvement options. Evaluation of resource criticality was integrated into the methodology for evaluation of Cleaner Production. Simple additive weighting (SAW) was used to solve the multi-criteria decision-making problem. The previous study on the natural resources that are imported to Lithuania revealed that metals are among the most important raw materials in terms of economic importance, supply, and environmental risks. Therefore, a typical metal processing company in Lithuania was selected for the detailed investigation of technological processes and Cleaner Production possibilities. The selected company processes about 3000 tons of various metals per year. The results of Process Material Flow Analysis show that most of the metal waste is generated during the metal plate cutting process (about 30.3 % of total metal consumption). Three resource efficiency improvement alternatives were evaluated and compared. The suggested decision support system was tested in order to decide on a definitive solution. The results reveal that evaluation of resource criticality in terms of geostrategic supply risk and economic importance can be used as an advantageous criterion to support the prioritization of Cleaner Production alternatives.     

Bootstrap approach for supplier selection based on production yield

Current manufacturing industries have increased their level of out-sourcing and relied more heavily on their supply chain as a source of competitive advantage. Supplier selection decisions have become an important component of production management. Those decisions have a significant impact on a firm's marketing competition, and suppliers may account for a large portion of the production cost. Production quality is one of the key factors in supplier evaluation. The manual of supplier certification includes a discussion of process capability analysis, which recommends a procedure for evaluating the most prevalent process capability index C _pk. However, the recommended procedure is applicable only when evaluating an individual supplier's performance. In this paper, we apply the bootstrap method to the supplier selection problem. We construct lower confidence intervals for the capability difference and ratio between two given suppliers. Performance comparisons are made among various bootstrap methods in terms of error probability and selection power. For convenience of applications, the sample sizes required for various designated selection power are also tabulated.     

Supplier evaluation and selection: an augmented DEA approach

Evaluating and selecting suppliers is an essential part of effectively managing today's dynamic and global supply chains. In this paper, we propose a supplier evaluation and selection methodology based on an extension of data envelopment analysis (DEA) that can evaluate suppliers in an efficient manner. Through the incorporations of a range of virtual standards, the proposed methodology termed augmented DEA, has enhanced discriminatory power over basic DEA models to rank suppliers. In addition, weight constraints are introduced to reduce the possibility of having inappropriate input and output factor weights. We demonstrate the application of augmented DEA with comparison experiments and find that the augmented DEA model has advantages over the basic DEA model as well as the cross-efficiency and super-efficiency models. Finally, we present a case application with data obtained from a communication and aviation electronics company to demonstrate the applicability and use of augmented DEA.     

Quantitative evaluation of cleaner production and environmental policy toward the co-benefit of greenhouse gas and odor reduction: case study of Tapioca starch industry

Chemical components of airborne volatile organic compounds (VOCs) released from a wastewater treatment system of the tapioca industry were identified. Quantitative analysis of the concentrations and the emissions of each chemical were evaluated taking into consideration the difference in atmospheric turbulence over the surface of the wastewater during the day and the nighttime periods. The chamber experiments were performed on-site in order to reflect actual environmental characteristics of the study area. Chemical concentrations were analyzed following the U.S. EPA TO-15 Standard Method. Emissions of each compound were calculated using the box model scheme. It was found that acetaldehyde and acetone were two major compounds of released airborne VOCs from the wastewater treatment system of the tapioca industry. Due to its high organic content, the wastewater treatment facilities of this type of factory generally caused the odor problem to its surrounding communities. These data were then used to evaluate the success of implementing the Clean Development Mechanisms project in this industry. Reduction in the affected area from odor by improving the wastewater treatment system from opened lagoons which is the type of common practice in most of the tapioca factories in the developing countries to the modified covered lagoons was evaluated. These results supported the theory of the co-benefit of managing both local environmental problems and reduction of greenhouse gas emissions from the implementation of cleaner technology in the agro-industry. This methodology can be applied to reveal and quantify the success of other green efforts particularly in the agro-industry businesses.

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Genetic algorithm with adaptive and dynamic penalty functions for the selection of cleaner production measures: a constrained optimization problem

This paper presents a new approach of genetic algorithm (GA) to solve the constrained optimization problem. In a constrained optimization problem, feasible and infeasible regions occupy the search space. The infeasible regions consist of the solutions that violate the constraint. Oftentimes classical genetic operators generate infeasible or invalid chromosomes. This situation takes a turn for the worse when infeasible chromosomes alone occupy the whole population. To address this problem, dynamic and adaptive penalty functions are proposed for the GA search process. This is a novel strategy because it will attempt to transform the constrained problem into an unconstrained problem by penalizing the GA fitness function dynamically and adaptively. New equations describing these functions are presented and tested. The effects of the proposed functions developed have been investigated and tested using different GA parameters such as mutation and crossover. Comparisons of the performance of the proposed adaptive and dynamic penalty functions with traditional static penalty functions are presented. The result from the experiments show that the proposed functions developed are more accurate, efficient, robust and easy to implement. The algorithms developed in this research can be applied to evaluate environmental impacts from process operations.     

Application of gray correlation analysis for cleaner production

The current methods used to select the schemes for cleaner production in China have some disadvantages. This paper presents research on gray correlation analysis with application to one cement factory in Chongqing, China. The results show that the gray correlation analysis can effectively avoid the subjective bias on the scheme selection for cleaner production. Schemes for cleaner production selected by the gray correlation analysis have better performance than those selected by the traditional method based on economic, environmental and technical indices.     

Materials selection for an automotive structure by integrating structural optimization with environmental impact assessment

Sustainable product development of an automotive structure requires a balanced approach towards technological, economical and ecological aspects. Current paper shows the application of a structural optimization system to the optimal choice of foams as a core material for sandwiches with aluminum alloy faces, for the use as floor panels in the bottom structure of a concept car. The minimization problem for the weight of the entire bottom structure under static load conditions, including stiffness, strength and buckling constraints, is formulated and solved for each material application. In addition to optimal (minimized) mass and materials' price used for selection of foams, the assessment of an environmental impact of materials-candidates during the entire life cycle of the structure is considered.     

An approach to systematic materials selection

An approach to systematic materials selection is believed to be suitable for both manual and computer aided materials selection. The procedure is divided into two stages; the discriminating and the optimising parts. In the former, all requirements on properties which do not influence the final sizing of the component in question are considered. From this stage a number of materials survives which are used in the optimisation stage. To rank the materials, merit parameters are introduced. This is exemplified for pressurized containers. With the help of the merit parameters it is possible to decide which material is the most suitable in a given situation. A procedure is also proposed from which the influence of the design parameters on the selection can be evaluated. This is exemplified by analysing how the pressure in the containers affects the choice of optimum material.     

Materials selection with several sizing variables taking environmental impact into account

In two recent papers by the authors in Materials and Design it was shown how efficient materials optimisation can be performed in realistic design cases with several sizing (geometrical) variables. In the present paper this analysis is expanded to take environmental impact into account. Two approaches are considered for the materials optimisation. In the first one, the environmental impact is considered as a constraint and the solution in found with the help of a control area diagram (CAD). In the second approach trade-off values for the environmental impact are used. The approaches are applied to a pressure vessel where the geometry is defined by four geometrical variables. Four pressure vessel steels and three aluminium alloys are used in the analysis. Merit indices and merit exponents are systematically used to solve the material optimisation problem. As expected the optimum material is strongly dependent on the chosen target functions and constraints. It is demonstrated that the two approaches for materials optimisation give identical results.     

Social sustainable supplier evaluation and selection: a group decision-support approach

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model.     

Material selection for microelectronic heat sinks: An application of the Ashby approach

This paper focuses on optimal materials selection for microelectronic heat sinks to maximize the thermal, mechanical and electronic response based on electro-thermal heat transfer analysis using the Ashby approach. In this work, material indices have been developed for a number of properties of heat sinks supported by materials selection tables/graphs. It is found that aluminum based alloys/metals perform better than other available materials for microelectronic heat sinks.     

An exact approach for portfolio selection with transaction costs and rounds

We consider a single-period mean-safety portfolio selection problem with transaction costs and integer constraints on the quantities selected for the securities (rounds). We propose an exact approach based on the partition of the initial problem into two subproblems and the use of a simple local search heuristic to obtain an initial solution. To the best of our knowledge, no optimal algorithms have been proposed in the literature for this problem. The proposed approach is simple, general and easily adaptable to other problems. An extensive experimental analysis based on real data from the main international Stock Exchange Markets is performed. The results show, on average, an impressive improvement with respect to the computational time and space memory required by CPLEX 7.0. We also show that the solution of the first subproblem can be used on its own as an extremely effective heuristic.     

An AHP-based water-conservation and waste-reduction indicator system for cleaner production of textile-printing industry in China and technique integration

The textile-printing industry in China makes an important contribution to the national economy. However, the associated pollution problems have caused gradual deterioration to the environment and adverse impacts on the local community. The indicator system of cleaner production gives a powerful tool to measure the level of cleaner production of textile-printing enterprises. In China, it has been a big problem of the textile-printing enterprise that consuming large amounts of fresh water and discharging large number of pollutants, and it is lacking in a scientific water-conservation and waste-reduction cleaner production evaluation system. To solve such problems, the establishment of water-conservation and waste-reduction cleaner production indicator system in textile-printing industry is proposed and assessed by the means of analytic hierarchy process (AHP) in this article. The judgement matrix is then determined with the Delphi Method combined. Finally, with the Yaahp software, the weight of each indicator is obtained. As an effective way to save water resource and reduce waste emission, the cleaner production technique integration is provided for the enterprises to solve the above problems and achieve the goals of saving water and decreasing the amount of disposed pollutants.     

An economic off-line quality control approach for unstable production processes

An economic off-line inspection/disposition approach is proposed, which incorporates manufacturing variation. This approach includes a new inspection algorithm for inspections based on cost minimization and utilizing a specified confidence level for identifying in-control items. This approach addresses two situations not addressed in previous papers: (i) the last unit in the batch is conforming; (ii) inspection time is non-negligible. Advantages are that there is no need to record the original position of each unit, the impact of manufacturing variation is reduced and non-negligible inspection times can be easily incorporated. Comparisons of this approach to other approaches are provided.     

An online approach to dynamic rescheduling for production planning applications

Manufacturing firms must often consider how to plan the production of a new order while containing the impact on the existing plan. Two approaches are typically used to solve the problem: online scheduling and rescheduling. State-of-the-art for both strategies is analyzed and methods available in the literature are proved to be inefficient for real world cases coming from production planning problems in a manufacturing firm. We propose an alternative approach combining the most effective aspects of both traditional approaches. The already available production plan and the characteristics of the new order to be planned are studied and used in order to generate a new production plan that meets two requirements: containing the number of changes to the existing plan and minimizing the delays due to the newly planned order. Constraint programming is used to implement the proposed approach. Results on case studies are also provided to evaluate the effectiveness of the proposed approach.