Manoj Kumar Tiwari

Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach

Abstract With the emergence of a business era that embraces ‘change’ as one of its major characteristics, manufacturing success and survival are becoming more and more difficult to ensure. The emphasis is on adaptability to changes in the business environment and on addressing market and customer needs proactively. Changes in the business environment due to varying needs of the customers lead to uncertainty in the decision parameters. Flexibility is needed in the supply chain to counter the uncertainty in the decision parameters. A supply chain adapts the changes if it is flexible and agile in nature. A framework is presented in this paper, which encapsulates the market sensitiveness, process integration, information driver and flexibility measures of supply chain performance. The paper explores the relationship among lead-time, cost, quality, and service level and the leanness and agility of a case supply chain in fast moving consumer goods business. The paper concludes with the justification of the framework, which analyses the effect of market winning criteria and market qualifying criteria on the three types of supply chains: lean, agile and leagile.

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.

Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach

Activities in reverse logistics activities are extensively practiced by computer hardware industries. One of the important problems faced by the top management in the computer hardware industries is the evaluation of various alternatives for end-of-life (EOL) computers. Analytic network process (ANP) based decision model presented in this paper structures the problem related to options in reverse logistics for EOL computers in a hierarchical form and links the determinants, dimensions, and enablers of the reverse logistics with alternatives available to the decision maker. In the proposed model, the dimensions of reverse logistics for the EOL computers have been taken from four perspectives derived from balanced scorecard approach, viz. customer, internal business, innovation and learning, and finance. The proposed approach, therefore, links the financial and non-financial, tangible and intangible, internal and external factors, thus providing a holistic framework for the selection of an alternative for the reverse logistics operations for EOL computers. Many criteria, sub-criteria, determinants, etc. for the selection of reverse logistics options are interrelated. The ability of ANP to consider interdependencies among and between levels of decision attributes makes it an attractive multi-criteria decision-making tool. Thus, a combination of balanced scorecard and ANP-based approach proposed in this paper provides a more realistic and accurate representation of the problem for conducting reverse logistics operations for EOL computers.

Implementing the Lean Sigma framework in an Indian SME: a case study

Lean and Six Sigma are two widely acknowledged business process improvement strategies available to organisations today for achieving dramatic results in cost, quality and time by focusing on process performance. Lately, Lean and Six Sigma practitioners are integrating the two strategies into a more powerful and effective hybrid, addressing many of the weaknesses and retaining most of the strengths of each strategy. Lean Sigma combines the variability reduction tools and techniques from Six Sigma with the waste and non-value added elimination tools and techniques from Lean Manufacturing, to generate savings to the bottom-line of an organisation. This paper proposes a Lean Sigma framework to reduce the defect occurring in the final product (automobile accessories) manufactured by a die-casting process. The proposed framework integrates Lean tools (current state map, 5S System, and Total Productive Maintenance (TPM)) within Six Sigma DMAIC methodology to enhance the bottom-line results and win customer loyalty. Implementation of the proposed framework shows dramatic improvement in the key metrics (defect per unit (DPU), process capability index, mean and standard deviation of casting density, yield, and overall equipment effectiveness (OEE)) and a substantial financial savings is generated by the organisation.

Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power Dispatch

Economic dispatch is a highly constrained optimization problem encompassing interaction among decision variables. Environmental concerns that arise due to the operation of fossil fuel fired electric generators, transforms the classical problem into multiobjective environmental/economic dispatch (EED). In this paper, a fuzzy clustering-based particle swarm (FCPSO) algorithm has been proposed to solve the highly constrained EED problem involving conflicting objectives. FCPSO uses an external repository to preserve nondominated particles found along the search process. The proposed fuzzy clustering technique, manages the size of the repository within limits without destroying the characteristics of the Pareto front. Niching mechanism has been incorporated to direct the particles towards lesser explored regions of the Pareto front. To avoid entrapment into local optima and enhance the exploratory capability of the particles, a self-adaptive mutation operator has been proposed. In addition, the algorithm incorporates a fuzzy-based feedback mechanism and iteratively uses the information to determine the compromise solution. The algorithms performance has been examined over the standard IEEE 30 bus six-generator test system, whereby it generated a uniformly distributed Pareto front whose optimality has been authenticated by benchmarking against the epsiv -constraint method. Results also revealed that the proposed approach obtained high-quality solutions and was able to provide a satisfactory compromise solution in almost all the trials, thereby validating the efficacy and applicability of the proposed approach over the real-world multiobjective optimization problems.

A fuzzy ANP-based approach to R&D project selection: A case study

Research and development (R&D) project selection is a complex decision-making process. It involves a search of the environment of opportunities, the generation of project options, and the evaluation by different stakeholders of multiple attributes, both qualitative and quantitative. Qualitative attributes are often accompanied by certain ambiguities and vagueness because of the dissimilar perceptions of organizational goals among pluralistic stakeholders, bureaucracy and the functional specialization of organizational members. Such differences in perceptions often hinder the attainment of consensus and coordination. Therefore, failures are frequent in R&D investment planning. To perceive the preferences of the various stakeholders and to map them into an analytical decision-making framework are challenging tasks. Further, risks and uncertainties are also associated with the investments and returns of R&D projects. This paper illustrates an application of fuzzy ANP (analytic network process) along with fuzzy cost analysis in selecting R&D projects. Fuzzy set theory is incorporated to overcome the vagueness in the preferences. The method adopted uses triangular fuzzy numbers for pair-wise comparison and applies extent analysis followed by defuzzification to determine the weights for various attributes.

Productivity improvement of a computer hardware supply chain

Purpose – To determine the key reverse logistics variables, which the top management should focus so as to improve the productivity and performance of computer hardware supply chains.Design/methodology/approach – In this paper, an interpretive structural modeling (ISM) based approach has been employed to model the reverse logistics variables typically found in computer hardware supply chains. These variables have been categorized under “enablers” and “results”. The enablers are the variables that help boost the reverse logistics variables, while results variables are the outcome of good reverse logistics practices.Findings – A key finding of this modeling is that environmental concern is the primary cause of the initiation of reverse logistics practices in computer hardware supply chains. For better results, top management should focus on improving the high driving power enabler variables such as regulations, environmental concerns, top management commitment, recapturing value from used products, resource...

Consensus-based intelligent group decision-making model for the selection of advanced technology

Consensus forming is a critical process in the present day computer assisted group decision-making (GDM) scenario. Most of the GDM problems are of strategic dimensions and get complicated due to their multi-criteria framework involving many subjective and quantitative factors. In this research, a technology selection problem has been considered for a manufacturing company. The problem has been modeled into a multi-person, multi-criteria and multi-preference scenario. Various preference modes have been transformed into Fuzzy Preference Relations. A soft consensus based group decision-making under linguistic assessments has been adopted here to eliminate the role of a moderator. To incorporate the offline/online characteristics in the re-evaluation phase of the discussion, a multi-agent system (MAS) based negotiation model is proposed to resolve a technology selection problem.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firm’s decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers’ performances meet the industry and environment standards with effective human resource.

Scheduling of flexible manufacturing systems: An ant colony optimization approach

Abstract The scheduling problem for flexible manufacturing systems (FMSs) has been attempted in this paper using the ant colony optimization (ACO) technique. Since the operation of a job in FMSs can be performed on more than one machine, the scheduling of the FMS is considered as a computationally hard problem. Ant algorithms are based on the foraging behaviour of real ants. The article deals with the ant algorithm with certain modifications that make it suitable for application to the required problem. The proposed solution procedure applies a graph-based representation technique with nodes and arcs representing operation and transfer from one stage of processing to the other. Individual ants move from the initial node to the final node through all nodes desired to be visited. The solution of the algorithm is a collective outcome of the solution found by all the ants. The pheromone trail is updated after all the ants have found out their respective solutions. Various features like stagnation avoidance and prevention from quick convergence have been incorporated in the proposed algorithm so that the near-optimal solution is obtained for the FMS scheduling problem, which is considered as a non-polynomial (NP)-hard problem. The algorithm stabilizes to the solution in considerably lesser computational effort. Extensive computational experiments have been carried out to study the influence of various parameters on the system performance.