Ming K. Lim

A meta-heuristic algorithm for heterogeneous fleet vehicle routing problems with two-dimensional loading constraints

The two-dimensional loading heterogeneous fleet vehicle routing problem (2L-HFVRP) is a variant of the classical vehicle routing problem in which customers are served by a heterogeneous fleet of vehicles. These vehicles have different capacities, fixed and variable operating costs, length and width in dimension, and two-dimensional loading constraints. The objective of this problem is to minimize transportation cost of designed routes, according to which vehicles are used, to satisfy the customer demand. In this study, we proposed a simulated annealing with heuristic local search (SA_HLS) to solve the problem and the search was then extended with a collection of packing heuristics to solve the loading constraints in 2L-HFVRP. To speed up the search process, a data structure was used to record the information related to loading feasibility. The effectiveness of SA_HLS was tested on benchmark instances derived from the two-dimensional loading vehicle routing problem (2L-CVRP). In addition, the performance of SA_HLS was also compared with three other 2L-CVRP models and four HFVRP methods found in the literature.

Benchmarking eco-efficiency in green supply chain practices in uncertainty

Benchmarking has not received much attention in the eco-efficiency literature because of the lack of an appropriate methodology to aid the electronic production process in green supply chain (GSC) practices. This study fills this analytical gap and suggests a rigorous quantitative approach for benchmarking eco-efficiency. However, there are qualitative and quantitative approaches to the eco-efficient criteria. Hence, this study undertakes fuzzy set theory within reference model (known as TODIM), a method that allows users to assess both qualitative and quantitative data together. This study is to aid traditional benchmarking activities and to provide guidance to practitioners and an example of a largest smart phone manufacturer across the globe to demonstrate the proposed technique with appropriate result to benchmark the eco-efficiency in GSC under uncertainty. TODIM is useful for identifying the best performing units against which to be benchmarked as well as for providing actionable measures for improvement of a firm’s performance. This study compares gain and loss functions as benchmarking tools in GSC practices. Implications for managers and directions for future research are discussed.

A Six Sigma and DMAIC application for the reduction of defects in a rubber gloves manufacturing process

Purpose – In this era of globalisation, as competition intensifies, providing quality products and services has become a competitive advantage and a need to ensure survival. The Six Sigmas problem-solving methodology DMAIC has been one of the several techniques used by organisations to improve the quality of their products and services. This paper aims to demonstrate the empirical application of Six Sigma and DMAIC to reduce product defects within a rubber gloves manufacturing organisation. Design/methodology/approach – The paper follows the DMAIC methodology to systematically investigate the root cause of defects and provide a solution to reduce/eliminate them. In particular, the design of experiments, hypothesis testing and two-way analysis of variance techniques were combined to statistically determine whether two key process variables, ovens temperature and conveyors speed, had an impact on the number of defects produced, as well as to define their optimum values needed to reduce/eliminate the defe...

Using a hybrid method to evaluate service innovation in the hotel industry

The process of evaluating perceptions (qualitative scale) and data from operations (quantitative scale) should be merged for service innovation analysis.Hybrid MCDM methods (TFNs, TODIM and Choquet integral) deal with dependence relations and the shortcomings. This study develops a hybrid method to improve selection decision making in service innovation. Because criteria for customer perceptions tend to be vague and conflicting, the process of evaluating perceptions (qualitative scale) and operational data (quantitative scale) should be combined. This study proposes the concomitant evaluation of qualitative and quantitative scales using a hybrid approach that combines fuzzy set theory, a discrete multi-criteria method based on prospect theory (known as TODIM in Portuguese) and the non-addictive Choquet integral. The study assumes that the criteria possess interdependent relationships. The advantages of the proposed hybrid approach, which exhibits a hierarchical structure, have been demonstrated throughout the hot spring hotel industry. The proposed method demonstrates that it can be extremely useful for recommending operational alternatives because it clearly identifies the main criteria of the expressed alternatives. The results indicate that the approach easily and effectively accommodates criteria with gain and loss functions and can help practitioners improve their performance and reduce overall service innovation risks.

Production Planning for Hybrid Remanufacturing and Manufacturing System with Component Recovery

In this paper, we address component recovery under the condition of limited resources from the OEMs (Original Equipment Manufacturers) standpoint. We develop a linear programming model for a hybrid remanufacturing and manufacturing system for production planning problems with deterministic returns. In this paper, a data set from an OEM that both remanufactures and manufactures the products is used to demonstrate the performance of the proposed model. Subsequently, an analysis of the impact of the remanufactured product’s price and the quantity of returns on revenue and total cost will be discussed. We have found that uncertain factors of manufacturing influence the profit and uncertain factors of remanufacturing influence the production planning, such as the rate of the yield on component remanufacturing and the quantity of returns.

Lean and Green – Synergies, Differences, Limitations, and the Need for Six Sigma

Historically, profitability and efficiency objectives have been the prevailing interest for organisations. However, the move towards green operations has forced companies to seek alternatives to combine these with green objectives and initiatives. Green lean is the result of this combination. The purpose of this paper is to critically discuss the green lean approach and the potential benefits of integrating Six Sigma to enhance its effectiveness. The paper is based on a literature review that discusses the synergies and differences of lean and green, and its main limitations. Departing from the limitations identified, the paper then proposes Six Sigma, and specially its problem solving methodology DMAIC, as an approach that may help in overcoming the limitations of green lean. Thus, the paper conceptually proposes Green Lean Six Sigma. It intends to offer academics, researchers and practitioners interested in lean and green with some initial conceptual ideas regarding their possible integration with Six Sigma.

The role of social media data in operations and production management

Social media data contain rich information in posts or comments written by customers. If those data can be extracted and analysed properly, companies can fully utilise this rich source of information. They can then convert the data to useful information or knowledge, which can help to formulate their business strategy. This cannot only facilitate marketing research in view of customer behaviour, but can also aid other management disciplines. Operations management (OM) research and practice with the objective to make decisions on product and process design is a fine example. Nevertheless, this line of thought is under-researched. In this connection, this paper explores the role of social media data in OM research. A structured approach is proposed, which involves the analysis of social media comments and a statistical cluster analysis to identify the interrelationships amongst important factors. A real-life example is employed to demonstrate the concept.

Improving road transport operations through lean thinking: a case study

ABSTRACT Traditionally, logistics and transportation problems have been addressed through mathematical modelling, operations research, and simulation, but criticism has emerged about their effectiveness to actually address real-life problems. This paper documents a case study whereby the road transport operations of a leading Mexican brewery were improved through lean thinking and waste reduction. Two lean-based principles and tools were combined: the Seven Transportation Extended Wastes and Transportation Value Stream Mapping. Three systematic steps were proposed to facilitate the implementation of improvement. Feasibility studies conducted in this research suggested that lean thinking is an effective alternative for the improvement of road transport operations. The findings of this research could be used as guidance for transport managers to improve road transport operations. This paper also expands the limited evidence of the application of lean thinking in road transport logistics and highlights the research areas where its application has been concentrated in this sector.

Using a multi-agent system to optimise resource utilisation in multi-site manufacturing facilities

Due to cost economies and better serving the global market, many enterprises expanded their manufacturing environment from a localised, single-site facility to more globalised, multi-site facilities. In order to take advantage of operating multi-site facilities, it is vital to make optimisation decisions of resource utilisation as if these facilities situated across different geographical locations are one integrated facility and take into account of the extended multi-site constraints and variables. This paper proposes a multi-agent system, using its characteristics of autonomy and intelligence, to integrate process planning and production scheduling across different facilities, so as to secure the most efficient and cost-effective plan and schedule to meet the demand. A currency-based agent iterative bidding mechanism is developed to facilitate the co-ordination of agents to achieve the goal. A genetic algorithm is employed to tune the currency values for agent bidding. In this paper, a case study is used for simulation in order to demonstrate the effectiveness and performance of the proposed agent system.

A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand

In remanufacturing research, most researchers predominantly emphasised on the recovery of whole product (core) rather than at the component level due to its complexity. In contrast, this paper addresses the challenges to focus on remanufacturing through component recovery, so as to solve production planning problems of hybrid remanufacturing and manufacturing systems. To deal with the uncertainties of quality and quantity of product returns, the processing time of remanufacturing, remanufacturing costs, as well as market demands, a robust optimisation model was developed in this research and a case study was used to evaluate its effectiveness and efficiency. To strengthen this research, a sensitivity analysis of the uncertain parameters and the original equipment manufacturer’s (OEM’s) pricing strategy was also conducted. The research finding shows that the market demand volatility leads to a significant increase in the under fulfilment and a reduction in OEM’s profit. On the other hand, recovery cost reduction, as endogenous cost saving, encourages the OEM to produce more remanufactured products with the increase in market demand. Furthermore, the OEM may risk profit loss if they raise the price of new products, and inversely, they could gain more if the price of remanufactured products is raised.