Thi Diem Chau Le

In polyurethane (PU) casting lines, precise tracking of mold lifecycles governs both product quality and planning efficiency. Manual monitoring produces systematic count discrepancies and offers no mechanism to prevent overproduction or the continued use of structurally expired molds. This study proposes a dual-tier radio frequency identification (RFID) architecture in which a work-order execution tier bounds output by the planned quota while a lifecycle tier tracks each mold against a structural limit of 600 passes. Validating a pass requires the elapsed curing interval to fall inside a calibrated time gate and the accumulated count to remain below the quota. Because full-scale deployment is capital-intensive and disruptive to a continuous line, the architecture is evaluated ex ante through a stochastic discrete-event simulation of a ten-line, 120-mold casting shop, benchmarked against the incumbent manual policy over 25 replications. The simulation reveals a result not evident from the specification alone: time-gated validation on strict two-reader pairing attains only 90.26% (±0.07) mold-level pass-count accuracy at realistic on-metal detection probabilities, below the manual baseline of 93.52% (±0.04), because single-sided read losses are discarded as exceptions. Adding a finite-state recovery layer that reconstructs single-sided detections raises accuracy to 98.06% (±0.03) and holds it above 96% even at a per-reader detection probability of 0.90. Over a 120-day horizon the recovered architecture reduces expired-mold exposure by 59.3%, defects from expired molds by 75.7%, overproduction by 78.9% and planning labour by 90.4%. Sensitivity analysis further requires oven residence-time standard deviation to be held below approximately 1.0 min.

The current study proposes a new approach that is a combination of methods: fuzzy and decision-making trial and evaluation laboratory (DEMATEL) and distance-based approximation (DBA) so that decision-makers can determine the relationship structures between criteria, how the criteria affect each other, and the weight of each criterion. From that, managers can quickly and easily evaluate and select the best alternative. A previous study using DEMATEL and grey relational analysis (GRA) is presented as an example. Data from this previous study are used to present the implementation process and results of the proposed method and simultaneously show the results of the current problem solved by the fuzzy DEMATEL – TOPPSIS (technique for order of preference by similarity to ideal solution) method. The comparison of results between three methods including DEMATEL – GRA, fuzzy DEMATEL – TOPPSIS, and fuzzy DEMATEL – DBA is performed to demonstrate the efficiency of the proposed method. The results show that there is a slight difference in weights between fuzzy DEMATEL and DEMATEL but the error is extremely low. In addition, the correlation of results between methods is very high. Particularly, correlation coefficients between fuzzy DEMATEL and DEMATEL, between fuzzy DEMATEL – TOPPSIS and fuzzy DEMATEL – BDA, and between DEMATEL – GRA and fuzzy DEMATEL – BDA are 0.99, 0.95, and 0.78 respectively. Finally, all three methods suggest alternative 4 as the best option.

Background: Information sharing plays a key role in supply chain performance. According to previous individual studies, technology, trust, commitment, and uncertainty are four potential factors affecting information sharing. However, most studies focus on testing a positive relationship between each factor and information sharing. Therefore, it is necessary to evaluate the effect of each factor on information sharing. Objective: To determine the accurate effect of factors on sharing information and propose key factors to support decision-makers in improving their information sharing. Data: Correlation coefficients between factors are collected from 41 individual studies with a total of 8,983 samples on Google Scholar Methods: Using the rank correlation test and Egger’s regression test to test publication bias. The meta-analysis method is used to perform analysis models, including fixed-effect, random-effect, and Hunter and Schmidt methods Results: Commitment plays the most important role in information sharing when compared to technology, trust, and uncertainty. Commitment accounts for 19% in the Hunter and Schmidt method and 22% in both fixed-effect and random-effect models. In addition, the result indicates that there are around 50% of other factors that affect the efficiency of sharing information besides four factors in our studies. Conclusion: Technology, trust, and commitment significantly affect information sharing, of which the impact of commitment on information sharing is strongest and should be a priority in improving the effectiveness of information sharing. Our study contributes two findings to literature in the field of supply chain information sharing: 1) certain confirming the important role of commitment on sharing information, and 2) the necessity of considering other factors besides these four elements.

Supply chain structure of global enterprises tend to develop dramatically. These lead to more difficulty for enterprises in managing and building information sharing systems. Thus, it is a necessary for enterprises to limit the scope of the information sharing system by selecting essential partners. The aims of this study are to quantify the cooperation of each supply chain member, and evaluate and visualize their effects in information sharing systems in order to support policymakers in making their decisions in supply chain management. The network analytical method in network science is applied to indicate the relationship between supply chain members and present a comprehensive supply chain visually. Moreover, Motor Corporation’s topology in Japan is used as a representation of global enterprise features to analyze the relationships between supply chain members. The data for Motor Corporation is secondary data which includes the number of suppliers, manufacturers, and dealers, and the interaction among them. Data is collected and verified from reputable websites such as www.marklines.com, or www.statista.com. As a result, this study contributes by applying a new method for not only determining the impact levels of supply chain members but also giving visual descriptions of impact levels on the large-scale information sharing system.

Manufacturing supporting tool costly impacts on workstation capacity in furniture industry. A good design on supporting tool would contribute effectively on productivity but it is rarely focused as its importance. Product (supporting tool) should be designed with user-based approach (Conceive). User demands on the product will be transformed into its design. Implementation should be done to evaluate the effective of the supporting tool. Finally, it will be operated and evaluated on the real shop floor. This paper will present a research to design a supporting tool, a rotating table for collecting required materials, following the CDIO approach. The tool supports effectively on the job with potential improvement on productivity, operation and company expects.