Showing 1–12 of 53 results
A combined methodology for supplier selection and performance evaluation
Today, organizations that wish to carry on the sustainable growing need a robust strategic performance measurement and evaluation system because of changing demands of consumers, reduced product life cycle, competitive and globalised markets. In this study, a new methodology is introduced and proposed for increasing the supplier selection and evaluation quality. The new approach considers both qualitative and quantitative variables in evaluating performance for selection of suppliers based on efficiency and effectiveness in one of the biggest car manufacturing factory in Turkey. This new methodology is realized in two steps. In the first stage, qualitative performance evaluation is performed by using fuzzy AHP (Analytical Hierarchical Process) in finding criteria weights and then fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is utilized in finding the ranking of suppliers. So, qualitative variables are transformed into a quantitative variable for using in DEA (Data Envelopment Analysis) methodology as an output called quality management system audit. In the second stage, DEA is performed with one dummy input and four output variables, namely, quality management system audit ,warranty cost ratio, defect ratio, quality management. As a result, comparing with the present system applied by the car factory, the new method seems to be some advantages and superiorities for making the decision in buying the quality car luggage side part (panel) by selecting the suitable supplier(s) in an automotive factory of Turkey.
A mixed-integer non-linear program to model dynamic supplier selection problem
In a highly competitرایگان!
In a highly competitive scenario, suppliers play a vital role in making a business organization successful. Business of any organization is continuous process and therefore the supplier selection is also dynamic in nature. This is quite natural as the organization’s demand; supplier’s capacity, quality level, lead time, unit part cost and fixed transportation cost of supplier varies with time. Therefore, supplier identified for one period may not necessarily be same for the next period to supply the same set of parts. Hence, the supplier selection problem is highly dynamic in real practice. In this paper, a mixed-integer non-linear program (MINLP) is developed to address the dynamic supplier selection problem (DSSP). To validate the proposed MINLP data are generated randomly. A numerical illustration is also provided to demonstrate the proposed MINLP using LINGO.
A multi-criteria master production scheduling approach for special purpose machinery
This paper presentsرایگان!
This paper presents a multi-criteria master production scheduling approach as the final assembly of special purpose machines is known to be very cost intensive. These costs are mainly influenced by the master production schedule (MPS). Two major cost drivers arise. First, long assembly lead-times (up to several months) combined with high product values result in high capital commitments; thus, leadtimes need to be minimized. Moreover, the factory calendar must be considered while calculating the MPS because the factory calendar can significantly influence the resulting lead-times. Second, contractual penalties and compensation costs arise if confirmed delivery dates cannot be kept. Therefore, resource requirements must be accounted for, and an MPS that is executable on the assembly shop floor must be calculated. To increase planning flexibility, we do not restrict the resource utilization with a formal constraint; instead, we introduce the additional objective of resource leveling. Consequently, the conflicting objectives lead-time minimization and resource leveling are integrated into a single objective function, in which the decision maker’s preferences are represented by a weighting factor. To calculate such an MPS, we develop a tailor-made construction heuristic combined with a randomized variable neighborhood descent procedure. We evaluate our solution method by solving small instances with a commercial solver and large-scale instances from an application case of an aerospace company. Our results reveal that the decision maker’s preferences are adequately reflected by the weighting factor. Moreover, we can provide a rule of thumb for selecting an appropriate initial weighting factor.
A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context
Sustainable supply cرایگان!
Sustainable supply chain management (SSCM) has received much consideration from corporate and academic over the past decade. Sustainable supplier performance evaluation and selection plays a significant role in establishing an effective SSCM. One of the techniques that can be used for sustainable supplier performance evaluation and selection is data envelopment analysis (DEA). In real world problems, the inputs and outputs might be imprecise. This paper develops an integrated DEA enhanced Russell measure (ERM) model in fuzzy context to select the best sustainable suppliers. A case study is presented to exhibit the efficacy of the proposed method for sustainable supplier selection problem in a resin production company. The case study demonstrates that the proposed model can measure effectiveness, efficiency, and productivity in uncertain environment with different α levels. Also, it shows that the proposed model aids decision makers to deal with economic, social, and environmental factors when selecting sustainable suppliers.
A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods
Multiple criteria deرایگان!
Multiple criteria decision-making (MCDM) research has developed rapidly and has become a main area of research for dealing with complex decision problems. The purpose of the paper is to explore the performance evaluation model. This paper develops an evaluation model based on the fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution, fuzzy TOPSIS, to help the industrial practitioners for the performance evaluation in a fuzzy environment where the vagueness and subjectivity are handled with linguistic values parameterized by triangular fuzzy numbers. The proposed method enables decision analysts to better understand the complete evaluation process and provide a more accurate, effective, and systematic decision support tool.
A Web-based ERP system for business services and supply chain management: Application to real-world process scheduling
A Web-based ERP systرایگان!
A Web-based ERP system developed for attacking business problems and managing real-world business processes ranging from simple office automation procedures to complicated supply chain planning is presented. The system’s Web-aspect provides significant advantages, as the system is distributed through interoperable, cross-platform and highly pluggable Web-service components. The system involves a powerful workflow engine that manages the entire process event flow within the enterprise increasing efficiency and control at the same time. Business processes, when needed, are controlled by the enterprise quality management system and consequently the ISO directives are accurately followed. A real-world process scheduling system developed for the specific needs of Greek Construction Manufacturing Enterprises is illustrated as a detailed paradigm of the system’s capabilities. The problem was formulated to assign project tasks in form of lots to enterprise resources in order that resources idle time and delays in project preparation time were minimized. The problem was solved by a simple and effective heuristic algorithm.
An analysis of DEMATEL approaches for criteria interaction handling within ANP
Majority of the Multرایگان!
Majority of the Multiple-Attribute Decision Making (MADM) methods assume that the criteria are independent of each other, which is not a realistic assumption in many real world problems. Several forms of interactions among criteria might occur in real life situations so that more sophisticated/intelligent techniques are required to deal with particular needs of the problem under consideration. Unfortunately, criteria interaction concept is very little issued in the literature. It is still a very important and critical research subject for intelligent decision making within MADM. The present paper aims to put a step forward to fill this gap by depicting the general picture, which provides a classification of methods related to criteria interaction phenomenon, and discuss/review the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) hybridizations first time in the literature. DEMATEL and ANP hybridizations grab remarkable attention of decision analysis community in recent years and seem as one of the most promising approaches to handle criteria interactions in a MADM setting.
An Analysis of Particle Swarm Optimizers
Many scientific, engرایگان!
Many scientific, engineering and economic problems involve the optimisation of a set of parameters. These problems include examples like minimising the losses in a power grid by finding the optimal configuration of the components, or training a neural network to recognise images of people’s faces. Numerous optimisation algorithms have been proposed to solve these problems, with varying degrees of success. The Particle Swarm Optimiser (PSO) is a relatively new technique that has been empirically shown to perform well on many of these optimisation problems. This thesis presents a theoretical model that can be used to describe the long-term behaviour of the algorithm. An enhanced version of the Particle Swarm Optimiser is constructed and shown to have guaranteed convergence on local minima. This algorithm is extended further, resulting in an algorithm with guaranteed convergence on global minima. A model for constructing cooperative PSO algorithms is developed, resulting in the introduction of two new PSO-based algorithms. Empirical results are presented to support the theoretical properties predicted by the various models, using synthetic benchmark functions to investigate specific properties. The various PSO-based algorithms are then applied to the task of training neural networks, corroborating the results obtained on the synthetic benchmark functions.
An analytical framework for handling production time variety at workstations of mixed-model assembly lines
In recent years markرایگان!
In recent years market demands have shifted towards customized products. As a result many manufacturing companies face an increasing variety of their product range. As it is not profitable to install new assembly lines for each product, assembly lines have to be able to handle different products in batch size one. In literature these lines are called mixed-model lines. They follow the logical principal of flow production but are capable of producing different products while needing minimal modification of assembly processes at the workstations. While mixed-model lines help manufacturing companies handling product differences profitably, they result in a number of challenges for the production process. One major challenge is related to the varying assembly times at a single workstation due to different products. Actions have to be taken to cope with assembly time that is over cycle time, in order to avoid stops in a flow production. For economical reasons manufacturing companies have to be able to work at a high workload utilization on average. Therefore it is necessary to have a detailed look at the workstations’ situation regarding production time variety. To address this, an analytical framework for assembly lines, based on a mixed-model line principle, is given to identify workstations that face high complexity regarding production time variety. This analytical framework contains several aspects focusing on production time variety as drifting probability, utilization and statistical dispersion. By using this framework, companies can apply their actions and line balancing more precisely to the situation at a workstation. Thus, manufacturing companies are able to handle complexity effectively and to reach a high workload utilization in their mixed-model assembly line.
An empirical study of green supply chain management practices amongst UK manufacturers
Purpose – The purposرایگان!
Purpose – The purpose of this paper is to examine the extent and nature of greening the supply chain (SC) in the UK manufacturing sector; and the factors that influence the breadth and depth of this activity. Design/methodology/approach – Based on the findings from a sample of manufacturing organisations drawn from the membership of The Chartered Institute for Purchasing and Supply. Data are collected using a questionnaire, piloted and pre-tested before distribution with responses from 60 manufacturing companies. Findings – On average manufacturers perceive the greatest pressure to improve environmental performance through legislation and internal drivers (IDs). The least influential pressures are related to societal drivers and SC pressures from individual customers. Green supply chain management (GSCM) practices amongst this “average” group of UK manufacturing organisations are focusing on internal, higher risk, descriptive activities, rather than proactive, external engagement processes. Environmental attitude (EA) is a key predictor of GSCM activity and those organisations that have a progressive attitude are also operationally very active. EA shows some relationship to legislative drivers but other factors are also influential. Operational activity may also be moderated by organisational contingencies such as risk, size, and nationality. Research limitations/implications – The main limitation to this paper is the relatively small manufacturing sample. Practical implications – This paper presents a series of constructs that identify GSCM operational activities companies to benchmark themselves against. It suggests which factors are driving these operational changes and how industry contingencies may be influential. Originality/value – This paper explores what is driving environmental behaviour amongst an “average” sample of manufacturers, what specific management practices take place and the relationships between them.
Antecedents of Task Innovation: The role of Management Information Systems
In the current econoرایگان!
In the current economic crisis, organizations’ information processing capabilities are challenged by additional and diverse demands. In this context, banks attempt to develop and apply more sophisticated and comprehensive Management Information Systems (MISs), in order to exploit their innovation competences and build a sustainable competitive advantage. This paper explores the antecedents of task innovation, reflected on (MIS) effectiveness, which was operationalised by the Competing Value Model (CVM). CVM synthesizes four different schools of management in order to measure IS effectiveness: open system (OS), human relations (HR), internal process (IP) and rational model (RM). Drawing from a sample of 186 bank employees in Greece, a structural model has been built and estimated using Partial Least Squares. Findings reveal that the HR component characterized by interpersonal communication, group decision making, team collaboration and personalization is the most important predictor of task innovation (TI). The RM dimension of MIS effectiveness based on optimizing, goal setting and forecasting has an indirect effect on HR via the OS and IP elements. The rest MIS effectiveness components (OS, IP) are indirectly associated with task innovation, through HR dimension.
Application of the stage gate model in production supporting quality management
Product and processرایگان!
Product and process quality was and still is a key factor of success for manufacturing companies in the competitive global business environment. The stage gate model represents a well-established method for quality management in the product development domain. This paper discusses the application of the stage gate model in the domain of production. The two domains differ in certain areas, which has to be reflected by the adapted stage gate model. The preliminary findings of the two case studies, covering manufacturing and assembly processes, indicate that an adapted stage gate model may provide valuable support for product and process quality improvement. However, the success is strongly dependent of the right adaptation, taking the individual requirements, limitations and boundaries into consideration .