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This study aims to design and improve the plant layout of a ceramic factory by adopting Systematic Layout Planning (SLP) and the simulation technique. A ceramic company in northern Thailand is selected as a case study. Three ceramic products including roof tiles, wall tiles and dishware are studied due to their highest production volume. Through the SLP approach, information regarding the number of departments and machines, the area of the plant, the frequency of movement and the distance between each department is collected for the analysis of the relationship between departments. Two plant layout designs are then proposed; the first one is derived from the Computerized Relationship Layout Planning algorithm (CORELAP), and the second one is the process layout. For selecting the most appropriate layout design, five criteria are considered including total distance, the average total process time of each unit produced, ease of movement, material flow and safety. To determine the distance and the average total process time per unit, Distance-Based Scoring and simulation techniques are conducted while the ease of movement, material flow and safety are rated based on whether the company satisfies each criterion. Employing the weight scoring technique, the results report that the CORELAP layout is the most suitable for further implementation due to its highest weighted score equal to 2.536 while the process layout receives 2.386. Implementing the CORELAP layout can reduce the total distance by 16.76% while the average total process time per unit of the CORELAP layout is not significantly different at the significance level of 0.05 as compared to the existing layout.

Resource planning in service industries is a difficult task and quite different from resource planning in manufacturing. Revenue management is one concept used in service industries when capacity and inventory are challenging to identify. In this study, the company case study provides chilled storage areas for customers. Different products are served and service charging is calculated based on the product’s weight and storing time. Currently, the target revenue cannot be achieved. This study presents the application of revenue management in chilled storage area allocation. From a previous study, there were four classes of products based on their importance level as A, B, C and D. Among all classes, the cost of under and overestimating demand was calculated for setting up the area allocation by following the concept of revenue management. Monte Carlo simulation was applied to simulate the existing and improved systems. The simulation results indicated that the average daily revenue could be improved when the storage area allocated to the lowest priority class (class D) was limited to be equal to the average daily demand of class D. Applying the proposed policy can help in increasing yearly revenue by approximately 73,638.75 Thai Baht. Finally, the implementation of the proposed procedure was discussed under the concept of Logistics 4.0.

Current Applied Science and Technology, 20, 2, 198-207

This study aims to propose a conceptual design of infrastructures and facilities in the distribution center for frozen and chilled fishery products connecting lower northern provinces to the nearby countries. Firstly, several data were collected and analyzed including primary data and secondary data. Secondly, the activities were listed based on primary data and secondary data. Thirdly, the infrastructures and facilities are proposed that were listed from the activity analysis. Finally, the conceptual design was proposed for designing the infrastructures and facilities in the distribution center for frozen and chilled fishery products. The general function of infrastructures and facilities in the distribution center was firstly proposed. Then, the additional functions that might be integrated were proposed in which the additional functions consisted of retail function, light industrial function, and custom function. This study presented not only possible activities but also infrastructures and facilities in the distribution center for frozen and chilled fishery products to connect lower northern provinces to the nearby countries in which this lead to the development of the economic growth in Thailand and neighboring countries as well.

This study presents an outbound-vehicle analysis in traffic system of Chiang Mai University as a case study. In the previous work, a network optimization technique is applied for maximum flow problem to find the optimal number of opened gates that appropriate for the current number of vehicles in the campus. Based on the results of previous work, simulation model was conducted in this study to introduce uncertainty factors in the system. The proposed simulation model was verified and validated to confirm the rightness and validity. Then, the uncertainty of vehicle velocity was introduced to the model in the 1st scenario. The results obtained from the 1st scenario showed that the optimal solution from the previous work was not sufficient when the uncertainty was introduced. The 2nd scenario was conducted to improve the system. Finally, the results obtained from the last scenario presented that changing directions after drivers perceived the traffic jam can help in improving the system, but the probability of changing the direction should be greater than or equal to 40%. Realtime traffic information systems may be considered to solve the traffic jam, if the solution is affected on changing driver’s decision as 40% or greater than this value.

This study proposed the mathematical model to obtain the appropriate storage methods for raw material at a case study company. Three classes of raw material as A, B, and C were stored using three types of storage equipment: pallet, shelf, and roller rack. The optimal solution showed that 94.60% of the storage area was used for current volume of raw material. After that, the amount of raw material was increased by 20% due to the expected customer demand. The optimal solution cannot be obtained because the storage area was not sufficient. The optimal solution indicated that the current storage area can handle up to 13.6% increment. Then, the sensitivity analyses were carried out. The results from the tests showed that to handle 20% increment as forecast, an additional storage area of increment 128.55 m 2 should be added to the current.

This research is aimed to present how Material Flow Cost Accounting (MFCA) plays a role in waste reduction. The study was carried out as a case study at a textile factory in Chiang Mai, Thailand. Following the procedure of MFCA, a specific type of shirt was selected to be studied. Cost of the positive and negative products of each process are identified, starting from cutting, sewing, quality checking, dyeing, buttonhole drilling, and packing processes. The results from the MFCA analysis showed that the costs of the positive and negative products were 84.26% and 15.74%, respectively. The greatest portion of the negative product cost resulted from material cost was 14.73% from the total of 15.74%. Focusing on the material cost of the negative product, the cutting and sewing process made up 80% of the material cost of the negative product, in comparison to other processes. Thereafter, the cause–effect diagram was used to identify the main source of the material cost of the negative product at both the cutting and sewing processes. Data collection and analysis indicated that three sources of the material cost of the negative product at both the processes, were from the cutting and trimming procedures. Three improvement solutions were proposed, as follows: (1) reducing the gap between the pieces of pattern, (2) reducing the edge width of each piece of pattern, and (3) employing a new cloth-cutting table. The results from the MFCA calculation showed that the costs of the negative product from these three solutions had reduced to 8.51%, 4.57%, and 3.06%, respectively. Moreover, it was found that when three solutions were combined and used at the same time, the cost of the negative product reduced to 11.27%. Practically, the first solution was the only way that could be promptly applied without any investment. However, when additional investments are available for process improvement, the combination of the three solutions was the most effective way that should be seriously considered.

This study proposed an integrated method of three concepts: MFCA, DP, and MCDM in operations improvement. The proposed procedure starts from performing MFCA calculation to evaluate material losses along the current production line and identify operations that need to be improved. The cost of positive product can be calculated for each solution. This value was subsequently used in DP with two additional criteria as the amount of investment and the score of difficulty in implementation. Three criteria were transformed to single objective in DP for finding the optimal solution. To demonstrate the application of the proposed method, one small textile company was selected as a case study. The results showed that the optimal solution was to implement only two from three solutions that can help the company to increase the cost of positive product from 84.26% to 94.73% with less investment and score of the difficulty in implementation.

First-come first-served (FCFS) is a general policy for refrigerated truck sequencing. However, adopting FCFS makes a company case study to face long waiting times before loading goods and inadequate parking areas for waiting trucks. To solve these problems, six dispatching rules are considered: latest departure time (LDT), smallest critical ratio (CR), shortest processing time (SPT), longest processing time (LPT), priority queueing considering density of customers (PQ-C), and priority queueing considering traffic congestion (PQ-T). Six-month historical data of trucks were collected and used for evaluating each rule. The minimum value of a truck's waiting time can be obtained when PQ-T has been tested. The results showed that using PQ-T can reduce 11.04% of the total waiting time when compare to FCFS. PQ-T is recommended for refrigerated truck sequencing mobile application development. This application can automatically generate the daily truck sequence.

This research designed and implemented a supply chain risk management platform and applied it to a case study of reduced-fat Lanna pork sausage as a new product development project. The proposed framework has three stages: risk identification, risk assessment, and risk mitigation. Seventeen risk agents with 17 risk events were identified based on SWOT analysis and the Porter Five Forces concept through the process of planning, sourcing, making and delivering, partially captured from the supply chain operations reference model in the first stage. In the second stage, an house of risk (HOR) framework was applied to present the impacts of each risk agent. In the third stage, eight risk agents with high impact were selected to design 21 preventive actions. Finally, three preventive actions with the highest effectiveness to difficulty ratio scores-‘sales evaluation of familiar products’, ‘increasing distribution channels and promotions to improve sales’, and ‘work flow improvement for work safety’-were then recommended for this new product development.

This study presented the process of new product development for processed parboiled-rice product using the concept of House of Quality (HoQ) from Quality Function Deployment (QFD) technique. The main tasks were Voice of Customer (VOC) surveying and HoQ development. From VOC, the form of new product was identified as processed parboiled-rice porridge product. The results from HoQ indicated that three aspects were concerned, packaging quality that should be able to maintain quality of food inside the package and prevent the contamination and market place. VOCs were linked into product technical specifications (TS) through relationship matrix between each consumer requirements (CR) and TS, the absolute importance value (Abs.IMP) and relative importance value (Rel.IMP) were calculated. As a results from Rel.IMP found that packaging design (score = 16.05%), type and quantity of raw material (score = 11.13%) and color and appearance of packaging (score = 9.77%) will be firstly consider in the development of parboiled rice porridge product.

This study aimed to present the robustness evaluation of job-shop scheduling based on Theory of Constraints (TOC) concept under processing time and demand variations using simulation technique. The performance of schedule based on TOC and traditional method (minimizing Cmax) were compared in terms of schedule robustness and performance. Simulation test scenarios were carried out by applying different distributions of processing time with two case problems as single and double bottlenecks cases. In addition, demand variation was added to the simulation test at the last experiment to increase the system variation. The results showed that the schedule based on TOC concept was superior to the schedule from traditional method when the variation in both processing time and demand were increased and the production system was more complicated as can be observed from the results of double bottlenecks case.

This study presents an application of adaptive particle swarm optimization (APSO) to solving the bi-level job-shop scheduling problem (JSP). The test problem presented here is 10×10 JSP (ten jobs and ten machines) with tribottleneck machines formulated as a bi-level formulation. APSO is used to solve the test problem and the result is compared with the result solved by basic PSO. The results of the test problem show that the results from APSO are significantly different when compared with the result from basic PSO in terms of the upper level objective value and the iteration number in which the best solution is first identified, but there is no significant difference in the lower objective value. These results confirmed that the quality of solutions from APSO is better than the basic PSO. Moreover, APSO can be used directly on a new problem instance without the exercise to select parameters.

This study aimed to propose a new formulation for the university course timetabling problem (UCTTP) when a day and time pattern is introduced. The day and time pattern would be set by the university and all assigned courses should follow this pattern. The different points of the proposed formulation would structure the model using starting and ending timeslots instead of a single timeslot to deal with courses with consecutiveness, periodic repeat, and multi-period sessions. To present the effectiveness of the proposed model, three test cases were solved and the results showed that the number of variables and constraints reduced with less computational time. Then, the case study was solved with multiple objectives based on goal programming (GP). The results of the case study show that the number of assignments during the undesirable time was minimised and that the total satisfaction score of all the lecturers was improved.

This study highlights a different systematic approach to the application of Theory of Constraints (TOC). The work describes the decisions involved in the implementation of TOC in a job-shop environment as a bi-level multi-objective mathematical model. On the first level, the decision is made by minimising idle time on the bottleneck to generate the initial schedule. The second level decision is to improve additional performance measurements by applying the multi-objective technique, while maintaining the bottleneck sequence obtained from the first level decision. Moreover, the concept of transfer lot is also adopted in this model to reduce the waiting time on each machine by allowing overlapped operations. The concept of transfer lot is applied as the constraint on earliest starting time for each job on each machine in the proposed mathematical model. Additionally, the machine set up time and product demands are also adopted to make the model practical to use in the real situation. The numerical examples ...

The objective of this research was to study the effect of applying direct or indirect cost allocation methods in Material Flow Cost Accounting (MFCA) analysis. Meatball production was selected as the case study. The direct method focused on the processes with large quantities of waste for improvement, without regard to the cost of the material wasted. On the other hand, the indirect method, which allocates cost based on the cost of materials, focused on the processes with the most costly waste in its improvement solutions. Thus, the different methods of cost allocation could target different process(es) for improvement. When materials used in a target product had the same cost and the quantity of waste was easily measured in the same unit, the direct and indirect cost allocation methods provided similar results. But when input materials differed in their costs and measurement units, the indirect cost allocation method was recommended.

This study aimed to present an application of Material Flow Cost Accounting (MFCA) to discover loss in the process and dynamic programming in decision making of improvement solutions. The research focused on internal supply chain operations of the case study. Based on MFCA analysis, the overall cost can be classified as the cost of positive product as 46.97% and the cost of negative product as 53.03%. The highest cost of negative product was material cost (MC) 45.52% following by system cost (SC) 6.41%, and energy cost (EC) 1.10% of the total product cost. The improvement solutions were proposed for MC reduction. Industrial engineering problem solving tools; cause and effect diagram, pareto diagram and why-why analysis, were used to investigate root causes for negative MC. Seven improvement solutions were proposed and evaluated based on MFCA calculation. The decision making was carried out using dynamic programming when the incursion was formulated using the cost of positive product increased by each solution. Finally, only the 1st, 2nd, 6th and 7th solution were selected and the cost of positive product can be increased from 46.97% to 56.08% and the cost of negative product reduced from 53.03% to 43.92%

This chapter presents application of material flow cost accounting (MFCA) analysis technique in meatball production. MFCA was used to analyze 6 processes that focused on the cost of positive and negative product occurred along the target production line. The results of MFCA analysis for existing process showed that the main negative product cost was material cost (MC). Thus, the improvement solution was proposed to reduce the cost of negative product of MC. The main material waste occurred at the first process of raw material preparation when melted ice occurred during the temperature reduction during raw material preparation step. To reduce this wastewater from melted ice, the proposed solution was to add a refrigerator instead of using ice for temperature reduction. By this method, the results from MFCA analysis showed that negative material quantity at raw material preparation step was reduced from 47.77 to 3.62 % that gave effects on negative MC reduction from 4.98 to 4.20 %. Consequently, this solution can help in saving production cost as 67,406.67 Baht per year when considering only this product.

This study presents the application of storage assignment in warehouse management to the case study of a plastic bag manufacturer located in Thailand. The objective is to evaluate the performance of the two methods: (1) using mathematical model and (2) class-based policy. The studied warehouse had one I/O point with 287 storage units dedicated for 62 products. The results of the mathematical model gave 51,317.45 meters per month as a minimum total traveling distance. The class-based policy gave 55,394.46 meters per month. Currently, non-systematic approach gave 71,921.38 meters per month (reduction from mathematical model and class-based methods were 28.65% and 22.98% respectively). The results from mathematical model is the optimal solution but to implement this policy, information technology such as warehouse system management was recommended to support workers during picking and receiving products.

This research aimed to present mathematical model for warehouse storage assignment to optimize total traveling distance. In this study, traveling distance was a three-axis traveling distance considering horizontal and vertical distance. The objective function of the model was to minimize the total traveling distance in order-picking process. To formulate the objective function, parameter of warehouse layout as width of aisle and storage row, length and height of storage block were included. The proposed model was tested by solving the numerical example of 3 products with 48 storage blocks and 3-level racks using Lingo software. The results showed that the total distance was 623.59 m. Product 2 had the highest ratio of number of pickings and storage blocks needed comparing among three products, thus this product was assign to the locations near I/O point. The results can ensure that the proposed model was able to give a valid solution and practical to apply for the real case problem in further study.

ing model based on multiple regression techniques, with enter, forward, back- ward, and stepwise selection methods were adopted, and these methods yielded mean absolute percentage error (MAPE) values of 18.39%, 25.63%, 21.21%, and 25.63%, respectively. These results demonstrate that multiple regression with the enter selection method is practical to predict the quantity of supply of off-season longan.

This research aims to apply the Material Flow Cost Accounting (MFCA) for process improvement of the target product, 950 cc. plastic water bottles, a case study company in Thailand. The production line of this product consists of five processes, crushing, mixing, blow molding, printing, and packing. The data collection was carried out for all processes and analyzed based on MFCA procedure. During the process of MFCA, quantity of input and output material, material cost, system cost and energy cost were presented. Then, the cost of positive and negative products can be distinguished based on mass balancing for all processes. The results from MFCA calculation showed that the highest negative product cost occurred at blow molding process. Then, the operations flow at blow molding process was analyzed using motion study and ECRS concept in order to eliminate production defects. Finally, the improvement solution was proposed and the results showed that the defects were reduced 26.07 % from previous negative product cost.

This paper presents a review on the Theory of Constraints (TOC) and quality improvement. TOC is one of the continuous improvement concepts that were developed to improve more competitive advantages in entities e.g. price/ cost, product quality, delivery reliability. From all literature reviews addressed here, two groups can be classified: first group research on TOC as a continuous improvement and second group research on TOC combined with other improvement policies such as lean and Six Sigma. The result of the later showed remarkable improvement comparing with the first group. Future researches on TOC will directed towards improving about the combination of TOC and other techniques in operations management and quality improvement.

This paper presents the application of simulation-based procedure to identify bottleneck in a job-shop environment. Ten jobs ten machines job-shop problem (10×10 JSP) is used to test the simulation-based procedure for identifying the system bottleneck. The result from the case shows that the choice of confidence interval level (CL) used in throughput mean comparison has effect on the bottleneck selection. Two scenarios are presented with two different CL of throughput mean, 75% CL and 90% CL. The result from the experiment shows that when % CL is increased, the judgment of bottleneck identification can be changed. Thus, it is necessary to use appropriate number of replications to match with the required %CL used in the simulation. In general, more replications are necessary when higher percentage of confidence interval level is required.

This study presents a simulation-based procedure to identify bottleneck station(s) related to Theory of Constraints (TOC). Bottleneck identification starts by running simulation model of existing system to collect data of the utilization of each machine/process and the time between arrivals and departures of each machine/process. Three factors, the machine/process utilization, the process utilization factor (ρ) and the product bottleneck rate (Rb) are used to identify potential bottleneck candidates. The real bottleneck must come from the process that has high value of two factors; the utilization of machine/process and the utilization factor and low value for the bottleneck rate. The simulation is used again to evaluate the solution by increasing capacity of a bottleneck candidate. If no improvement in throughput is observed, then the station is not a bottleneck and the procedure is run again using the other bottleneck candidate. Numerical examples are given to illustrate the proposed procedure in both case of single bottleneck and multiple bottlenecks.

This study presents an application of particle swarm optimisation (PSO) algorithm for a bi-level multi-objective job-shop scheduling problem. The bi-level decision-making requirement stems from the concept of theory of constraints. At the first level, the decision is made by concentrating on minimising idle time on the system bottleneck. The second-level decision is made to plan other machines while maintaining the maximum use of the bottleneck and gaining improvements in other performance measures. This paper proposed a PSO-based procedure for solving the bi-level programming problem. The proposed procedure simplifies the solution method by simultaneously providing solutions for the objective of both levels. In addition, during the schedule generation process, the job-shop case applied in this study also considers the machine set-up time, transfer lot size and product demands to make the model more realistic. The numerical examples are given to demonstrate how this approach works. The results from this procedure are compared with the solutions obtained by a commercial optimiser, the LINGO 10 software package. This proposed PSO is implemented in C# programming language in order to obtain the final solution within the short computational time.