23 research outputs found

    APPLICATION OF NEAR INFRARED SPECTROSCOPY FOR ENDPOINT DETERMINATION OF BLENDING AND INFLUENCE OF LOADING ORDER

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    Objective: This study aimed to apply near-infrared spectroscopy along with a thief as a tool to determine the endpoint of the blending process. Methods: The calibration model was constructed by partial least square regression. The best model was applied to determine the endpoint of the blending process, also the effect of loading order on the endpoint for the blending of the formulation containing a low concentration of the active pharmaceutical ingredient. Results: The best partial least square regression model yielded the lowest root mean square error of calibration of 1.4004, the lowest root mean square error of prediction of 1.4108 and the highest correlation coefficient of 0.9921. Validation study revealed the reference values were not statistically different from those of the predicted values. The model could predict the endpoint of the blending process with acceptable precision and accuracy. Standard deviation of the content of active pharmaceutical ingredients was â‰Ī 3% of the target after eighteen minutes of the blending process, which indicated the uniformity of powder blends. Additionally, the model revealed the order of powder loading slightly affected the blending time. The protocol that loaded the active pharmaceutical ingredient first or last needed a longer time to achieve the uniformity of blend. Conclusion: NIR spectroscopy is the rapid and effective tools that could be applied to study the blending process in the pharmaceutical manufacturing

    The measures to improve the manufacturing process by using the lean concept for hard disk drive industry

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    In this paper, the lean manufacturing method using value stream mapping was adopted to investigate and analyst the value of activities throughout production processes in order to eliminate the production wastes. While the simulation technique was used to support decision for proposing measures to increase a firm productivity in the case study, a hard disk drive component manufacturer. The results shown that the purposed method could reduce production cycle time (takt time) from 21.18 to 19.89 s., workforces from 10 to 8, work-in-process about 60% and eliminate production bottleneck. That led to more efficiency (12.19% increase) in production line balancing, indicating more effective production lines. Furthermore, improvement of production process continued progressively in the step of adhesive dispensing and the one of drying the glue by UV light. It led to ability to control the amount of glue dispensing more effectively, increasing quantity of work (33%) (from one syringe of glue) from 3,078 into 4,104 pieces of work per syringe, and reducing cost of glue (25%)

    A Comparative of Mathematical Model for Solving the Optimal Lane Depth with the Infinite and the Finite Production Rate Model: A Case Study of the ABC Warehouse

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    āļ•āđ‰āļ™āļ—āļļāļ™āļāļēāļĢāļšāļĢāļīāļŦāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ”āđ‰āļēāļ™āļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļēāļ–āļ·āļ­āđ€āļ›āđ‡āļ™āļ•āđ‰āļ™āļ—āļļāļ™āļŦāļĨāļąāļāđƒāļ™āļĢāļ°āļšāļšāđ‚āļĨāļˆāļīāļŠāļ•āļīāļāļŠāđŒ āđ‚āļ”āļĒāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāļ–āļ·āļ­āļ§āđˆāļēāđ€āļ›āđ‡āļ™āļāļīāļˆāļāļĢāļĢāļĄāļŦāļĨāļąāļāļ‚āļ­āļ‡āļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļē āļ‹āļķāđˆāļ‡āđ‚āļ”āļĒāļ—āļąāđˆāļ§āđ„āļ›āļˆāļ°āļĄāļĩāļĢāļ°āļšāļšāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāļ—āļĩāđˆāļŦāļĨāļēāļāļŦāļĨāļēāļĒāļ•āļąāđ‰āļ‡āđāļ•āđˆāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļšāļšāļ§āļēāļ‡āļāļ­āļ‡āļ‹āđ‰āļ­āļ™āđ„āļ›āļˆāļ™āļ–āļķāļ‡āļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļšāļšāļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļī āļāļēāļĢāļĻāļķāļāļĐāļēāļ§āļīāļˆāļąāļĒāļ„āļĢāļąāđ‰āļ‡āļ™āļĩāđ‰āđ„āļ”āđ‰āļĻāļķāļāļĐāļēāļĢāļ°āļšāļšāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļšāļšāļ§āļēāļ‡āļāļ­āļ‡āļ‹āđ‰āļ­āļ™ āđ€āļ™āļ·āđˆāļ­āļ‡āļˆāļēāļāđ€āļ›āđ‡āļ™āļĢāļ°āļšāļšāļ—āļĩāđˆāđ„āļ”āđ‰āļĢāļąāļšāļ„āļ§āļēāļĄāļ™āļīāļĒāļĄ āļĄāļĩāļ„āļ§āļēāļĄāļĒāļ·āļ”āļŦāļĒāđˆāļ™āļļ āļŠāļđāļ‡āļ•āđ‰āļ™āļ—āļļāļ™āļ•āđˆāļģ āđ€āļŦāļĄāļēāļ°āļāļąāļšāļŠāļīāļ™āļ„āđ‰āļēāļ—āļĩāđˆāļĄāļĩāļ­āļąāļ•āļĢāļēāļāļēāļĢāļŦāļĄāļļāļ™āđ€āļ§āļĩāļĒāļ™āļŠāļđāļ‡ āđāļĄāđ‰āļ§āđˆāļēāļˆāļ°āđ€āļāļīāļ”āļ„āļ§āļēāļĄāļŠāļđāļāđ€āļ›āļĨāđˆāļēāļ‚āļ­āļ‡āļžāļ·āđ‰āļ™āļ—āļĩāđˆāđ‚āļ”āļĒāļĢāļ§āļĄāļĄāļēāļ āļ—āļģāđƒāļŦāđ‰āļĄāļĩāļ­āļĢāļĢāļ–āļ›āļĢāļ°āđ‚āļĒāļŠāļ™āđŒāļ”āđ‰āļēāļ™āļžāļ·āđ‰āļ™āļ—āļĩāđˆāļ•āđˆāļģ āļāļēāļĢāļ­āļ­āļāđāļšāļšāļĢāļđāļ›āđāļšāļšāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāļ—āļĩāđˆāļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāđ‚āļ”āļĒāļāļēāļĢāļāļģāļŦāļ™āļ”āļ„āļ§āļēāļĄāļĨāļķāļāļŠāđˆāļ­āļ‡āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāļ—āļĩāđˆāđ€āļŦāļĄāļēāļ°āļŠāļĄāļ–āļ·āļ­āđ€āļ›āđ‡āļ™āđāļ™āļ§āļ—āļēāļ‡āļŦāļ™āļķāđˆāļ‡āđƒāļ™āļāļēāļĢāđāļāđ‰āļ›āļąāļāļŦāļē āļ­āļĒāđˆāļēāļ‡āđ„āļĢāļāđ‡āļ•āļēāļĄ āļāļēāļĢāļāļģāļŦāļ™āļ”āļ„āļ§āļēāļĄāļĨāļķāļāļŠāđˆāļ­āļ‡āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāļ āļēāļĒāđƒāļ•āđ‰āļ­āļąāļ•āļĢāļēāļāļēāļĢāđ€āļ‚āđ‰āļēāļĄāļēāļ‚āļ­āļ‡āļŠāļīāļ™āļ„āđ‰āļēāļ—āļĩāđˆāļˆāļģāļāļąāļ”āļĒāļąāļ‡āđ„āļĄāđˆāļ„āđˆāļ­āļĒāļžāļšāđƒāļ™āļāļēāļĢāļĻāļķāļāļĐāļēāļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļˆāļķāļ‡āđ„āļ”āđ‰āđƒāļŠāđ‰āļ•āļąāļ§āđāļšāļšāļ„āļ“āļīāļ•āļĻāļēāļŠāļ•āļĢāđŒāļŠāļģāļŦāļĢāļąāļšāļāļēāļĢāļŦāļēāļ„āļ§āļēāļĄāļĨāļķāļāļŠāđˆāļ­āļ‡āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļē āđ„āļ”āđ‰āđāļāđˆ āļ•āļąāļ§āđāļšāļšāđ„āļĄāđˆāļˆāļģāļāļąāļ” āļ„āļ·āļ­āļ•āļąāļ§āđāļšāļšāļ„āļ“āļīāļ•āļĻāļēāļŠāļ•āļĢāđŒāļ—āļĩāđˆāđ„āļĄāđˆāļžāļīāļˆāļēāļĢāļ“āļēāļ­āļąāļ•āļĢāļēāļāļēāļĢāđ€āļ‚āđ‰āļēāļĄāļēāļ‚āļ­āļ‡āļŠāļīāļ™āļ„āđ‰āļē āļŦāļĢāļ·āļ­ P = ∞ āđāļĨāļ°āļ•āļąāļ§āđāļšāļšāļˆāļģāļāļąāļ” āļ„āļ·āļ­āļ•āļąāļ§āđāļšāļšāļ„āļ“āļīāļ•āļĻāļēāļŠāļ•āļĢāđŒāļ—āļĩāđˆāļĄāļĩāļāļēāļĢāļžāļīāļˆāļēāļĢāļ“āļēāļ­āļąāļ•āļĢāļēāļāļēāļĢāđ€āļ‚āđ‰āļēāļĄāļēāļ‚āļ­āļ‡āļŠāļīāļ™āļ„āđ‰āļēāļ”āđ‰āļ§āļĒ āļŦāļĢāļ·āļ­ P ≠ ∞ āđ€āļžāļ·āđˆāļ­āđ€āļ›āļĢāļĩāļĒāļšāđ€āļ—āļĩāļĒāļšāļ§āđˆāļēāļ„āļ§āļēāļĄāļĨāļķāļāļŠāđˆāļ­āļ‡āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāļˆāļēāļāļ•āļąāļ§āđāļšāļšāđƒāļ”āļˆāļ°āļ—āļģāđƒāļŦāđ‰āđ€āļāļīāļ”āļ„āļ§āļēāļĄāļŠāļđāļāđ€āļ›āļĨāđˆāļēāđ‚āļ”āļĒāļĢāļ§āļĄāđ€āļ‰āļĨāļĩāđˆāļĒāļ™āđ‰āļ­āļĒāļ—āļĩāđˆāļŠāļļāļ” āļ‹āļķāđˆāļ‡āļˆāļēāļāļāļēāļĢāļĻāļķāļāļĐāļēāļžāļšāļ§āđˆāļē āļ•āļąāļ§āđāļšāļšāļˆāļģāļāļąāļ”āđƒāļŦāđ‰āļ„āļ§āļēāļĄāļĨāļķāļāļŠāđˆāļ­āļ‡āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāļ—āļĩāđˆāļ—āļģāđƒāļŦāđ‰āđ€āļāļīāļ”āļ„āļ§āļēāļĄāļŠāļđāļāđ€āļ›āļĨāđˆāļēāļĢāļ§āļĄāđ€āļ‰āļĨāļĩāđˆāļĒāļ™āđ‰āļ­āļĒāļāļ§āđˆāļēāļ„āļ§āļēāļĄāļĨāļķāļāļŠāđˆāļ­āļ‡āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāļ—āļĩāđˆāđ„āļ”āđ‰āļˆāļēāļāļ•āļąāļ§āđāļšāļšāđ„āļĄāđˆāļˆāļģāļāļąāļ”Warehouse management costs are the major cost in the logistics system. The main activity in the warehouse is storage, which comes with different storage systems ranging from block stacking to automated storage. This study are concentrated on block stacking system, because of its widespread use, high flexibility, low cost and suitability for high inventory turnover. However, it causes potential loss of storage space within the warehouse that affects the facility's space utilization. Designing a block stacking system by determining the optimal lane depth is one way to solve the problem. However, studies on determining the optimal lane depth under the finite production rate constraint has not been carried out so far. This research applied two mathematical models to compute the optimal lane depth, the infinite model (P = ∞) does not consider the production rate but the finite model (P ≠ ∞) does in order to compare the average waste of storage space. It has been found that the finite model gives less average waste of storage space than its counterpart

    An Application of Genetic Algorithm to Determine Storage Method for Materials in AS/RS a Case Study of an ABC Automated Warehouse

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    āļšāļ—āļ„āļ§āļēāļĄāļ™āļĩāđ‰āļāļĨāđˆāļēāļ§āļ–āļķāļ‡āļĢāļ°āļšāļšāļˆāļąāļ”āđ€āļāđ‡āļšāđāļĨāļ°āđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™āļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļī (Automated Storage/Retrieval System; AS/RS) āļāļēāļĢāļāļģāļŦāļ™āļ”āļ§āļīāļ˜āļĩāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļĨāļ°āđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™āļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļīāļ—āļģāđ„āļ”āđ‰āļŦāļĨāļēāļĒāļ§āļīāļ˜āļĩāļ”āđ‰āļ§āļĒāļāļąāļ™ āļ—āļąāđ‰āļ‡āļāļēāļĢāļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļ‚āļ™āļēāļ”āļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļē āļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļĢāļđāļ›āđāļšāļšāļāļēāļĢāļĢāļąāļšāđ€āļ‚āđ‰āļēāļ‚āļ­āļ‡āļŠāļīāļ™āļ„āđ‰āļē āļĢāļ§āļĄāđ„āļ›āļ–āļķāļ‡āļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļāļēāļĢāđ€āļ„āļĨāļ·āđˆāļ­āļ™āļ—āļĩāđˆāļ‚āļ­āļ‡āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļˆāļąāļāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļĨāļ°āđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™ (S/R Machine) āļ”āļąāļ‡āļ™āļąāđ‰āļ™āļœāļđāđ‰āđƒāļŦāđ‰āļšāļĢāļīāļāļēāļĢāļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļē āļ•āđ‰āļ­āļ‡āđƒāļŦāđ‰āļ„āļ§āļēāļĄāļŠāļģāļ„āļąāļāđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļāļēāļĢāļāļģāļŦāļ™āļ”āļ§āļīāļ˜āļĩāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļĨāļ°āđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™āļ§āļąāļŠāļ”āļļāđ€āļžāļ·āđˆāļ­āđƒāļŦāđ‰āļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļŠāļđāļ‡āļŠāļļāļ” āļˆāļēāļāļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļēāļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļīāļšāļĢāļīāļĐāļąāļ—āļāļĢāļ“āļĩāļĻāļķāļāļĐāļēāļžāļšāļ§āđˆāļē āļĄāļĩāļŠāđˆāļ§āļ‡āđ€āļ§āļĨāļēāļ—āļĩāđˆāļŠāļīāļ™āļ„āđ‰āļēāđƒāļ™āļĢāļ°āļšāļšāļ–āļđāļāļĢāļąāļšāđ€āļ‚āđ‰āļē-āļ­āļ­āļāđƒāļ™āļŠāđˆāļ§āļ‡āđ€āļ§āļĨāļēāļ—āļĩāđˆāļ„āļēāļšāđ€āļāļĩāđˆāļĒāļ§āļāļąāļ™āđƒāļ™āļĨāļąāļāļĐāļ“āļ°āļ„āļģāļŠāļąāđˆāļ‡āđ€āļ”āļĩāđˆāļĒāļ§ (Single Command) āļ„āļīāļ”āđ€āļ›āđ‡āļ™āļĢāđ‰āļ­āļĒāļĨāļ° 52.20 āļ‹āļķāđˆāļ‡āļāđˆāļ­āđƒāļŦāđ‰āđ€āļāļīāļ”āļ„āļ§āļēāļĄāļŠāļđāļāđ€āļ›āļĨāđˆāļēāđƒāļ™āļāļēāļĢāļ”āļģāđ€āļ™āļīāļ™āļāļēāļĢāļ‚āļ­āļ‡ S/R Machine āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āđ„āļ”āđ‰āļĻāļķāļāļĐāļēāđ€āļžāļ·āđˆāļ­āļāļģāļŦāļ™āļ”āļ§āļīāļ˜āļĩāļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļš āđāļĨāļ°āđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™āđƒāļ™āļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļēāđ‚āļ”āļĒāļĄāļļāđˆāļ‡āđ€āļ™āđ‰āļ™āđ„āļ›āļ—āļĩāđˆāļāļēāļĢāļĨāļ”āđ€āļ§āļĨāļēāđƒāļ™āļāļēāļĢāļ—āļģāļ‡āļēāļ™āļ‚āļ­āļ‡ S/R Machine āļœāļđāđ‰āļ§āļīāļˆāļąāļĒāđ€āļĨāļ·āļ­āļāļ§āļīāļ˜āļĩāļāļēāļĢāļ—āļģāļ‡āļēāļ™āđāļšāļšāļ„āļģāļŠāļąāđˆāļ‡āļ„āļđāđˆ (Dual Command) āļ„āļ·āļ­ āļāļēāļĢāļ—āļĩāđˆāđƒāļŦāđ‰ S/R Machine āļ™āļąāđ‰āļ™āļŠāļēāļĄāļēāļĢāļ–āļ—āļģāļ‡āļēāļ™āđ„āļ”āđ‰āļ—āļąāđ‰āļ‡āļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāļŠāļīāļ™āļ„āđ‰āļēāđāļĨāļ°āļāļēāļĢāđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™āļŠāļīāļ™āļ„āđ‰āļēāđƒāļ™āļāļēāļĢāđ€āļ”āļīāļ™āļ—āļēāļ‡āđ€āļžāļĩāļĒāļ‡ 1 āļĢāļ­āļšāļ„āļģāļŠāļąāđˆāļ‡ āđ‚āļ”āļĒāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļ§āļīāļ˜āļĩāļ—āļēāļ‡āļžāļąāļ™āļ˜āļļāļāļĢāļĢāļĄ (Genetics Algorithms; GA) āđƒāļ™āļāļēāļĢāļāļģāļŦāļ™āļ”āļ•āļģāđāļŦāļ™āđˆāļ‡āđƒāļ™āļāļēāļĢāļˆāļąāļ”āđ€āļāđ‡āļšāđāļĨāļ°āđ€āļĢāļĩāļĒāļāļ„āđ‰āļ™āđ€āļ›āļĢāļĩāļĒāļšāđ€āļ—āļĩāļĒāļšāļāļąāļšāļ§āļīāļ˜āļĩāļĢāļđāļ›āđāļšāļšāđ€āļŠāļīāļ‡āļ„āļ“āļīāļ•āļĻāļēāļŠāļ•āļĢāđŒ (Math Model) āļœāđˆāļēāļ™āļāļēāļĢāļ—āļ”āļĨāļ­āļ‡āļ—āļēāļ‡āļ•āļąāļ§āđ€āļĨāļ‚āļāļąāļšāļ›āļąāļāļŦāļēāļ„āļĨāļąāļ‡āļŠāļīāļ™āļ„āđ‰āļēāļ‚āļ™āļēāļ”āđ€āļĨāđ‡āļ āļāļĨāļēāļ‡ āđāļĨāļ°āđƒāļŦāļāđˆ āļžāļšāļ§āđˆāļēāļ§āļīāļ˜āļĩāļāļēāļĢāļ—āļĩāđˆāļ™āļģāđ€āļŠāļ™āļ­āđƒāļŠāđ‰āđ€āļ§āļĨāļēāđƒāļ™āļāļēāļĢāļ„āļģāļ™āļ§āļ“āđ€āļžāļ·āđˆāļ­āļŦāļēāļ„āļģāļ•āļ­āļšāļ—āļĩāđˆāļ”āļĩāļ—āļĩāđˆāļŠāļļāļ”āļ™āđ‰āļ­āļĒāļāļ§āđˆāļēāđāļĨāļ°āđ„āļ”āđ‰āļ„āļģāļ•āļ­āļšāļ—āļĩāđˆāđ€āļ‚āđ‰āļēāđƒāļāļĨāđ‰āļ„āđˆāļēāļ—āļĩāđˆāļ”āļĩāļ—āļĩāđˆāļŠāļļāļ” (Near Optimum)This article discusses about the features of Automated Storage/Retrieval Systems. There are several ways to define automated storage and retrieval methods such as improving warehouse sizes, improving consolidated goods receipt patterns and improving the movement of the Storage/Retrieval machine (S/R machine). The warehouse operator must consider the determination of how materials are stored and retrieved for maximum efficiency. According to a case study of an automated warehouse, the time when goods in the system were in and out during the overlapping period as a single command accounted for 52.20%, causing operational waste of the S/R machine. This research study aims to define warehouse storage and retrieval methods with a focus on reducing the operating time of the S/R machine. We apply a dual command method in which the S/R machine can work for both storage and retrieval operations in just one cycle. We applied Genetics Algorithms (GA) to determine storage location and retrieval compared with the math model, through experiments with small, medium and large warehouses problems. It was found that the proposed method took less time to obtain the near optimum solution

    The Application of Cellular Manufacturing in Hard Disk Drive Industry

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    AbstractCellular Manufacturing System (CMS) is used widely in multiple-product industries because CMS is the management of cells for flexibility of production system. Processes or machines are arranged in similar groups, and products are categorized in appropriate production groups. This study used CMS to apply to the hard disk drives industry. The goal is to increase productivity but decrease work flow distance by utilizing the management algorithm of cells. The group of cells yielded from this algorithm will be used in CMS, and the measure of performance for the groups of cells management are grouping efficacy, inter-cell production flow, and work flow distance. The systems of before and after applying CMS are simulated in order to investigate the change in production. There are two significant results obtained from this study. Four out of six product types improved in production: 2.29%, 16.22%, 3.39%, and 4.16%. In addition, the work flow distance of six product types decreased: 46.80%, 41.41%, 45.95%, 7.63%, 2.66%, and 13.61%

    āļāļēāļĢāđ€āļžāļīāđˆāļĄāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļŠāļēāļĒāļāļēāļĢāļ›āļĢāļ°āļāļ­āļšāđ‚āļĢāđ€āļ•āļ­āļĢāđŒ āļāļĢāļ“āļĩāļĻāļķāļāļĐāļē āđ‚āļĢāļ‡āļ‡āļēāļ™āļœāļĨāļīāļ•āļŠāļīāđ‰āļ™āļŠāđˆāļ§āļ™āļĒāļēāļ™āļĒāļ™āļ•āđŒ ABC An Efficiency Improvement of the Rotor Assembly Line: A Case Study ABC Automotive Parts Factory

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    āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āđ€āļžāļīāđˆāļĄāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļāļēāļĢāļ—āļģāļ‡āļēāļ™āļ‚āļ­āļ‡āļŠāļēāļĒāļāļēāļĢāļ›āļĢāļ°āļāļ­āļšāđ‚āļĢāđ€āļ•āļ­āļĢāđŒ āđ‚āļ”āļĒāļāļēāļĢāļĨāļ”āđ€āļ§āļĨāļēāļ—āļĩāđˆāđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļˆāļąāļāļĢāļŦāļĒāļļāļ”āļ—āļģāļ‡āļēāļ™ (Machinery Downtime) āļ‹āļķāđˆāļ‡āļĄāļĩāļŠāļēāđ€āļŦāļ•āļļāļŦāļĨāļąāļāļĄāļēāļˆāļēāļ āļ‚āļąāđ‰āļ™āļ•āļ­āļ™āļāļēāļĢāđ€āļĢāļīāđˆāļĄāļ•āđ‰āļ™āļ‡āļēāļ™āđāļĨāļ°āļāļēāļĢāļ•āļĢāļ§āļˆāļŠāļ­āļš (Startup work & inspection) āļ—āļĩāđˆāđ€āļāļīāļ”āļ‚āļķāđ‰āļ™āļ—āļļāļāļ§āļąāļ™ āļĢāļ§āļĄāļ—āļąāđ‰āļ‡āļ•āļģāđāļŦāļ™āđˆāļ‡āļāļēāļĢāļ—āļģāļ‡āļēāļ™āļ—āļĩāđˆāđ„āļĄāđˆāđ€āļŦāļĄāļēāļ°āļŠāļĄ āđ‚āļ”āļĒāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļĄāļ·āļ­āļ„āļļāļ“āļ āļēāļž 7 āļŠāļ™āļīāļ” (7 QC Tools) āļāļēāļĢāļˆāļąāļ”āļŠāļĄāļ”āļļāļĨāļŠāļēāļĒāļāļēāļĢāļœāļĨāļīāļ• (Line Balancing) āđāļĨāļ°āļāļēāļĢāļ§āļēāļ‡āļœāļąāļ‡āđ‚āļĢāļ‡āļ‡āļēāļ™ (Plant Layout) āļĄāļēāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđāļĨāļ°āļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļāļĢāļ°āļšāļ§āļ™āļāļēāļĢāļœāļĨāļīāļ• āļˆāļēāļāļāļēāļĢāļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļ”āđ‰āļ§āļĒāļ§āļīāļ˜āļĩāļāļēāļĢāļ—āļĩāđˆāļ™āļģāđ€āļŠāļ™āļ­āļžāļšāļ§āđˆāļēāļŠāļēāļĄāļēāļĢāļ–āļĨāļ”āđ€āļ§āļĨāļēāļ—āļĩāđˆāđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļˆāļąāļāļĢāļŦāļĒāļļāļ”āļ—āļģāļ‡āļēāļ™ āļĨāļ‡āļˆāļēāļ 24.14 āļ™āļēāļ—āļĩ āđ€āļŦāļĨāļ·āļ­ 10.76 āļ™āļēāļ—āļĩ āļ„āļīāļ”āđ€āļ›āđ‡āļ™ 55.43% āļŠāđˆāļ‡āļœāļĨāđƒāļŦāđ‰āļŠāļēāļĄāļēāļĢāļ–āđ€āļžāļīāđˆāļĄāļˆāļģāļ™āļ§āļ™āļāļēāļĢāļœāļĨāļīāļ•āđ„āļ”āđ‰ 10,512 āļŠāļīāđ‰āļ™āļ•āđˆāļ­āļ›āļĩ āđāļĨāļ°āļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļŠāļēāļĒāļāļēāļĢāļœāļĨāļīāļ•āļ‚āļ­āļ‡āļ‚āļąāđ‰āļ™āļ•āļ­āļ™āļāļēāļĢāđ€āļĢāļīāđˆāļĄāļ•āđ‰āļ™āļ‡āļēāļ™āđāļĨāļ°āļāļēāļĢāļ•āļĢāļ§āļˆāļŠāļ­āļš āđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™āļˆāļēāļ 41.53% āđ€āļ›āđ‡āļ™ 63.62% āļŠāđˆāļ‡āļœāļĨāđƒāļŦāđ‰āļ­āļąāļ•āļĢāļēāļāļēāļĢāļ—āļģāļ‡āļēāļ™āļ‚āļ­āļ‡āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļˆāļąāļāļĢ (Machine utilization) āđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™āļˆāļēāļāļ„āđˆāļēāđ€āļ‰āļĨāļĩāđˆāļĒ 75.62% āđ€āļ›āđ‡āļ™ 80.13%The objective of this research is to increase the efficiency of the rotor assembly line by reducing machinery downtime. This is mainly due to procedures for startup and inspection that occur every day together with inappropriate working positions by applying 7 QC tools, production line balancing, and plant layout to analyze and improve the production process. From the implementation of the proposed method, it was found that the machine downtime can be reduced from 24.14 minutes to 10.76 minutes, equivalent to 55.43%, resulting in an increase in the production of 10,512 pieces per year. Moreover, the efficiency of the startup work and inspections process, increased from 41.53% to 63.62%, resulting in the machine utilization rate increasing from an average of 75.62% to 80.13%

    An improvement of agricultural equipment manufacturing by using lean techniques : A case study of agricultural machinery company

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    The objective of this research was to study and improve the manufacturing process of agricultural equipment to reduce wastes by using the LEAN tools: a case study of agricultural machinery company. This study found that the main wastes were inefficiency of transportation and working process. The Systematic Layout Planning Pattern (SLP) had been applied. Moreover, the principles of ECRS, the change in input factors (a number of employees), together with simulation and the Analysis Hierarchy Process (AHP) were also used to determine the appropriate plant layout alternatives by considering the factors such as the productivity, materials handling distance, facilities utilization, and space utilization. The result shared that the best suitable layout is the layout No. 1. Then more improvement the layout No. 1 with the ECRS and the change of input factors (the amount of employees) ,it was found that increased productivity by 16.10%, increased facilities utilization by 15.73% and decreased materials handling distance by 48.12%. Furthermore, the number of employees and the average time of workpiece in system could be reduced from 7 to 6 persons, and 54.41 minutes to 45.65 minutes respectively

    Complete Cocrystal Formation during Resonant Acoustic Wet Granulation: Effect of Granulation Liquids

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    The manufacturing of solid pharmaceutical dosage forms composed of cocrystals requires numerous processes during which there is risk of dissociation into parent molecules. Resonant acoustic wet granulation (RAG) was devised in an effort to complete theophylline–citric acid (THPCIT) cocrystal formation during the granulation process, thereby reducing the number of operations. In addition, the influence of granulation liquid was investigated. A mixture of anhydrous THP (drug), anhydrous CIT (coformer), and hydroxypropyl cellulose (granulating agent) was processed by RAG with water or ethanol as a granulation liquid. The purposes were to (i) form granules using RAG as a breakthrough method; (ii) accomplish the cocrystallization during the integrated unit operation; and (iii) characterize the final solid product (i.e., tablet). The RAG procedure achieved complete cocrystal formation (>99%) and adequately sized granules (d50: >250 μm). The granulation using water (GW) facilitated formation of cocrystal hydrate which were then transformed into anhydrous cocrystal after drying, while the granulation using ethanol (GE) resulted in the formation of anhydrous cocrystal before and after drying. The dissolution of the highly dense GW tablet, which was compressed from granules including fine powder due to the dehydration, was slower than that of the GE tablet
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