Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP). After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP), namely the HGP model, was tested. Finally, the vehicle routing problem (VRP) for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA) which hybridizes the push forward insertion heuristic (PFIH), genetic algorithm (GA) and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation efficiently in this case.

In a continuous manufacturing environment where production and consumption occur simultaneously, one of the biggest challenges is the efficient management of production and inventory system. In order to manage the integrated production inventory system economically it is necessary to identify the optimal production time and the optimal production reorder point that either maximize the profit or minimize the cost. In addition, during production the process has to go through some natural phenomena like random breakdown of machine, deterioration of product over time, uncertainty in repair time that eventually create the possibility of shortage. In this situation, efficient management of inventory & production is crucial. This paper addresses the situation where a perishable (deteriorated) product is manufactured and consumed simultaneously, the demand of this product is stable over the time, machine that produce the product also face random failure and the time to repair this machine is also uncertain. In order to describe this scenario more appropriately, the continuously reviewed Economic Production Quantity (EPQ) model is considered in this research work. The main goal is to identify the optimal production uptime and the production reorder point that ultimately minimize the expected value of total cost consisting of machine setup, deterioration, inventory holding, shortage and corrective maintenance cost.

The purpose of this study is to provide criteria for selecting operations managers at the ‘service encounter’ for mobile telecommunication companies, and develop a system for this multi-criteria decision-making scheme based on the Analytical Hierarchy Process (AHP). There are three main criteria for evaluating the capability of service-encounter operation managers: (1) the ability to design service process; (2) the ability to operate service process; (3) the ability to conduct improvement. The AHP operation manager selection tool was developed based on the complex problems at the service encounter. It was created as a decision support system which was used to recruit and evaluate operations managers’ capability for the purpose of career advancement.

The new method to chart the Hodges-Lehmann estimator control chart is proposed in this study. The evaluation of the three nonparametric control charts - the Sign test (ST), Mann-Whitney (MW), and the Hodges-Lehmann estimator (HL), for the known process distribution using normal and Weibull data represent the symmetric and asymmetric shapes of the process based on the original method through the 10000 run lengths simulation. The result illustrates that the average run length performance of the ST and MW correspond to their respective test statistics but for HL’s performance, the result indicates that the average run length is much greater than that derived from Wilcoxon signed rank statistics. The Hodges-Lehmann estimator control chart by the new approach for the known process distribution will be the alternative method for the process that needs to robust outliers’ properties from this statistics. In addition, the simulation demonstrates that the performances of the Sign test (ST) from mean and median processes are varied in the skewed distribution, and moreover, the Sign test (ST) from the median process represents more accurate performance. Meanwhile, for the control groups, MW generated within control limits or without restriction shows slightly different performance. The performance of dual scheme for the above-mentioned variable parameters control charts also produce the weighted average values that effect from the tight control scheme to the regular control scheme.

This paper presents a methodology to improve the strength or the Modulus of Rupture (MOR) of fibre cement. The Six Sigma approach with the DMAIC steps was applied to a case study company. This research started from defining problem, setting the project objective and the project scope. Next, the measurement system was analyzed and the process map was set up. The potential factors of the problem was then determined. Due to there were many factors that affect the MOR, the Cause and Effect Matrix and the Failure Mode and Effect Analysis technique were then used to reduce the number of factors to be studied further. Next, three process factors, which were the pulp slurry freeness, the film-layer thickness, and the pressure step, were optimized using the results from the Box-Behnken experimental design. Other 13 remaining factors were improved by creating or revising the standard work instructions and training the operators. After that, the statistical process control and the control plan were set up to control the production processes. After improvement, the process capability index (Ppk) significantly increased from 0.26 to 1.35.

There is a high risk of R & D based innovation being commercialized, especially in the innovation transfer process which is a concern to many entrepreneurs and researchers. The purpose of this research is to develop the criteria of R & D commercialization capability and to propose a combined technique of Structural Equation Modelling (SEM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for R & D project evaluation. The research utilized a mixed-method approach. The first phase comprised a qualitative study on commercialization criteria development though the survey research of 272 successful entrepreneurs and researchers in all industrial sectors in Thailand. The data was collected with a structured questionnaire and analyzed by SEM. The second phase was involved with SEM-TOPSIS technique development and a case study of 45 R & D projects in research institutes and incubators for technique validation. The research results reveal that there were six criteria for R & D project commercialization capability, these are arranged according to the significance; marketing, technology, finance, non-financial impact, intellectual property, and human resource. The holistic criteria is presented in decreasing order on the ambiguous subjectivity of the fuzzy-expert system, to help with effectively funding R & D and to prevent a resource meltdown. This study applies SEM to the relative weighting of hierarchical criteria. The TOPSIS approach is employed to rank the alternative performance. An integrated SEM-TOPSIS is proposed for the first time and applied to present R & D projects shown to be effective and feasible in evaluating R & D commercialization capacity.

This paper provides a method of acoustic emission (AE) technique to detect a train bearing fault of tapered bearing unit (TBU). An approach is to utilize acoustic emission signals which were captured from piezoelectric transducer and processed using Fourier transform. The transformed signals may contain unique characteristic features relating to the various types of bearing faults. The experiments on different operating conditions were investigated and they corresponded to (a) a normal bearing and (b) outer race defect bearing. The result is promising for faulty bearing identification and discrimination between different bearing conditions.

This article provides a method of acoustic emission (AE) technique to detect leakage in pipeline and locate the position of the leakage. The AE sensor is made of piezoelectric effect transducer to pick up the acoustic emission signal which is generated from the turbulent flow at the leak position. The signal conditioning unit is used to enhanced and eliminate the background noise from the leak location sources. The main acoustic emission processing unit is used to acquire and process the extracted AE characteristic parameters from preprocessing waveform. The leak pipeline is simulated by drilling the hole and plugged with M8 screw at different locations. The results show that the proposed AE method can detect and locate simultaneous leak condition in pipeline with promising results.

An innovative price plan monitoring and advisory system simulates subscriber usage consumption for offering suitable price plan. The aim of this paper is to develop the decision support system by using Statistical Process Control (SPC) to identify subscriber usage behavior and provide critical visibility into subscriber consumption to detect their inappropriate usage especially in exceeding usage. To explore subscriber usage behavior, a forecasting model and a regression is employed to identify related factors and predictive usage model. The innovative price plan monitoring and advisory system has been verified and validated with one of the largest telecommunication company in Thailand. Using decision support system with effective control chart and real subscriber behavior pattern help mobile network operator grow their revenues and profits by offering an appropriate price plan as well as improve subscriber experience with more flexible choice to meet their individual usage consumption needs.

An important problem in control chart implementation is the availability of resources to collect and analyze data for control charts implementation. This paper proposes a method to prioritize and select final product parameters to control. The prioritization is based on cost of quality and technical criticality of those parameters. The prioritization method is demonstrated by a case study of flexible printed circuit manufacturing.