A heuristic based on Particle Swarm Optimisation (PSO) algorithm for solving VRPTW, which is an extension of PSO application for the Capacitated Vehicle Routing Problem (CVRP) (Ai and Kachitvichyanukul, 2007), is presented in this paper. A computational experiment is carried out by running the proposed algorithm with the VRPTW benchmark data set of Solomon (1987). The results show that the proposed algorithm is able to provide VRPTW solutions that are very close to its optimal solutions for problems with 25 and 50 customers within reasonably short of computational time

PurposeThis paper tries to generalize business process improvement (BPI) methodology. It utilizes the seven-waste framework as an essential step in the methodology. While the seven-waste concept is usually applied for manufacturing activities, this paper tries to explore the applicability of it to office-work activities. Also, this paper demonstrates that information technology can be used as a tool for reducing waste in the office-work.Design/methodology/approachA comprehensive literature review of BPI methodology studies was conducted in order to propose systematic flowcharts to represent the sequence of processes involved in each step of BPI methodology. The proposed flowcharts are applied to a case study in supply chain planning and allocation planning at a manufacturing company. The seven-waste framework is designed as part of the step, in which equivalency between the definition of waste found on the production floor and waste found in office work is presented.FindingsThe BPI methodology generally follows five steps: initialization, selection, design, implementation and evaluation. The seven-waste framework is effectively applied in the selection step. The case study shows that information technology can be used as a tool in business process improvement to reduce waste in the business process.Practical implicationsThe case study indicates that the proposed framework and methodology are proven able to reduce the three key performance indicators. They are the number of steps from 54 to 24 (55% reduction), processing time from 890 min to 313.5 min (64% reduction) and the number of the manual process from 41 to 17 (59% reduction).Originality/valueThis paper proposes a generalization of BPI methodology, the seven-waste framework in the selection step of the BPI methodology, the seven-waste concept in office-work activity and the use of information technology for BPI by reducing waste in office-work activity.

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PurposeThis paper aims to propose a framework on complaint management system for quality management by applying the text mining method and potential failure identification that can support organization learning (OL). Customer complaints in the form of email text is the input of the framework, while the most frequent complaints are visualized using a Pareto diagram. The company can learn from this Pareto diagram and take action to improve their process.Design/methodology/approachThe first main part of the framework is creating a defect database from potential failure identification, which is the initial part of the failure mode and effect analysis technique. The second main part is the text mining of customer email complaints. The last part of the framework is matching the result of text mining with the defect database and presenting in the form of a Pareto diagram. After the framework is proposed, a case study is conducted to illustrate the applicability of the proposed method.FindingsBy using the defect database, the framework can interpret the customer email complaints into the list of most defect complained by customer using a Pareto diagram. The results of the Pareto diagram, based on the results of text mining of consumer complaints via email, can be used by a company to learn from complaint and to analyze the potential failure mode. This analysis helps company to take anticipatory action for avoiding potential failure mode happening in the future.Originality/valueThe framework on complaint management system for quality management by applying the text mining method and potential failure identification is proposed for the first time in this paper.

Currently there is greater interest and an industrial need to create a bond between cast steel and aluminum alloys. The bond quality between these two metals must be considered, since it is affected by several casting techniques and parameters. This research aims to find the right combination of techniques and parameters to make a good bond between cast steel and aluminum alloys. This research systematically used the response surface methodology (RSM). Three important casting techniques and parameters are selected as independent variables, which are preheating temperature of cast steel, pouring temperature of aluminum alloy molten, and surface cleaning of cast steel. The gap between cast steel and aluminum alloy is used as dependent variable, which is defined as the quality measurement of the bond between two metals. The experiments were conducted on 48 samples, in which destructive test was performed in order to measure the gap. From the methodology, it is found that the recommended preheating temperature of cast steel is 491 °C, the recommended pouring temperature of aluminum alloy is 696 °C, and the recommended technique is cleaning the cast steel insert using degreasing. For practical purpose, the preheating temperature of cast steel can be set at 490 ± 10 °C and the pouring temperature of aluminum alloy can be set at 695 ± 10°C. This research limits on bimetal casting between cast steel and aluminum alloys, and the casting process is gravity die casting process. This paper is able to find the best casting techniques and parameters for cast steel and aluminum alloy bond using RSM. This paper also proposes gap bond between two metals as bond quality measurement.