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Predictive maintenance is one of the developments of maintenance activities to ensure the continuity of the production process, especially for companies with continuous production processes. However, predictive maintenance activities require support from other departments, one of which is the availability of spare parts. This study conducted an indepth analysis of 11 previous studies regarding joint or integration in predictive maintenance. Based on the results of the research, it is known that only a few joint or integration models in predictive maintenance are included in the use of a data-based approach to utilize data collected in real-time. Furthermore, this study proposes a framework that can be used in developing a data-driven joint predictive maintenance and inventory model of spare parts in multicomponents/ multi spare parts. [ABSTRACT FROM AUTHOR]

Sculptured dies cavity roughing (SDCR) is a multi-dimensional optimization problem that requires the simultaneous decision of several variables. The most frequent discussion in SDCR is the simultaneous decision on tool selection and cutting plane determination in order to minimize machining (roughing) time. This study consider the trade-off between roughing and finishing time which represented by residual volume in roughing process by applying machining efficiency as the objective of the proposed algorithm. The machining efficiency for each set of tool selection depend on the determination of cutting plane. Therefore this multi-dimensional problem is classified as a complex combinatorial problem and there is need for 2 dimensional problems formulation. This study proposed binary coding to represent the problem, by which enumeration of the problem could be well structured and the coding and decoding process of 2 dimensional problem could be simplified in order to search and identify the optimum result. The algorithm has produced the optimum result and empirically shown 10% of improvement of machining efficiency when compared to result from the simulator and better machining efficiency when compared to smallest-tool-possible (STP) and smallest residual possible (SRP). (Keywords : Sculptured dies cavity roughing, enumeration, binary coding, Fibonacci, climbing stairs problem) [ABSTRACT FROM AUTHOR]

This paper identifies the necessity of a Cyber-Physical Production System development for the Make-to-Order industry. The uniqueness of the Make-to-Order industry is that orders are low in production volume but wide in product variety. Thus, accurate and real-time data acquisition of the production activity is necessary to support decision-making to respond to customer orders and monitor production activities. The proposed Cyber-Physical Production System utilizes RFID and current sensors to identify the parts and machine activities. The Cyber-Physical Production System is proven cost-effective to the alternative controller-based Cyber-Physical Production System. Initial implementation has proven a viable solution and provides benefits to support decision-making in the Make-to-Order industry. [ABSTRACT FROM AUTHOR]

This paper identifies the necessity of a Cyber-Physical Production System development for the Make-to-Order industry. The uniqueness of the Make-to-Order industry is that orders are low in production volume but wide in product variety. Thus, accurate and real-time data acquisition of the production activity is necessary to support decision-making to respond to customer orders and monitor production activities. The proposed Cyber-Physical Production System utilizes RFID and current sensors to identify the parts and machine activities. The Cyber-Physical Production System is proven cost-effective to the alternative controller-based Cyber-Physical Production System. Initial implementation has proven a viable solution and provides benefits to support decision-making in the Make-to- Order industry. [ABSTRACT FROM AUTHOR]

This paper proposes a batch scheduling model where two time-changing effects simultaneously occur, i.e., parts deteriorating and operator learning-forgetting effects. A mathematical model is proposed for the problem where the decision variables are the number of batches, batch sizes, and a schedule of the resulting batches to minimize total actual flow time. A proposed algorithm is developed by trying different numbers of batches, starting from one and then increasing it one by one until the objective function value does not improve anymore. Numerical examples show that the faster operators learn, the lower the optimal number of batches and the lower the optimal total actual flow time. Second, the faster parts deteriorate, the higher the optimal number of batches and the higher the optimal total actual flow time. Finally, the model divides parts into small batches to prevent the processing time from increasing due to part deterioration. [ABSTRACT FROM AUTHOR]

Coordination members in supply chain need effective communication and information flows. One of tools which can support the coordination is agent-based model. In this study, it is considered independent partners consisting of one manufacturer and two suppliers which have individual decision for its production planning and the decision must be synchronize each other to achieve supply chain goal particularly to have higher service level for customer order. Agents represent supply chain members aforementioned who will exchange information and decision related to production planning. In this conceptual model, it will be described the production planning decision of individual participant which will be exchanged between supply chain members by agent-based modelling. Collaborative production planning is useful to achieve mutual benefit supply chain member by synchronizing their plan and deciding the most beneficial production planning. [ABSTRACT FROM AUTHOR]