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Abstract: Selection of proper materials for a diverse mechanism is one of the hardest tasks in the design and product improvements in various industrial applications. Materials play a vital and important function during the entire design and manufacturing process. The wrong selection of materials often leads to huge prices and ultimately results in product breakdown. Hence, the designers need to identify and select suitable materials with specific functionalities in order to attain the preferred output with the minimum cost concern and specific applicability. This paper tries to solve the materials selection problem by means of an expert system approach to manufacturing. According to this method either four or five different properties are inspected for each automotive part such as impact resistance, lightness, formability, corrosion resistance and low prices for bumpers; strength, formability, vibration absorption and low cost for flywheels; and strength, formability, corrosion resistance, biocompatibility and a small price for implants. Then, these were made more efficient using the expert system approach. Due to performing most of the above mentioned properties, polymeric materials {such as PP (polypropylene), HDPE (high density polyethylene) and PMMA (polymethyl methacrylate)} are selected for the bumpers; GFRPs (glass fiber reinforced plastics) and CFRPs (carbon fiber reinforced plastics) composites for high speed running, and cast iron and steel for low speeds for the flywheels; and finally stainless steel and polymeric materials {such as PVC (polyvinyl chloride) and PE (polyethylene)} were found to be the best materials for automotive parts. The selected materials were almost identical to those obtained by previous authors. [Copyright &y& Elsevier]

In job-shop production systems, orders are assigned to work centers according to their routes, and their operations are performed in this order. Production is becoming more and more complex with the increasing number of product lines and work centers with different routes. Decisions to be made according to the real-time monitoring of a dynamic production environment have become important. With the Fourth Industrial Revolution, information technologies are widely used in industries. A large amount of data is obtained from production tools that are capable of communicating with each other by means of Industry 4.0 and the internet of things. In this study, a simulation model of a production system that can collect data in real-time via sensors in work centers has been created and operation conditions have been determined. Then, work center / machine loading strategies were compared according to the delay periods of the jobs. The simulation model with the best loading strategy was run according to three different demand rates. Then data related with the delay status of the orders and the status of the work centers was obtained. The data were evaluated with data mining classification algorithms and rules were determined for delayed jobs. These rules were added to the simulation model as a decision mechanism. When an order is received in this model, the expert system estimates whether or not there will be a delay, and makes a decision to outsource the order's production if needed. This approach further reduces the number of delayed orders [ABSTRACT FROM AUTHOR]

A complex system is allow to able to be resolved by establishing a causal loop diagrams or explored by examining the dynamics of the system. Today, along with the development of technology, companies is also very good to be able to profit from the current system dominated, by the production planning very well, they need to keep customer satisfaction at the highest level. Companies will be able to stand in this way, but in a competitive environment. In this study, it is required to determine how a safety stock policy on sales volumes made, it has been made in the detections and predictions about this system affected by which dynamics. Causal loop diagram is developed for a textile company. This company's safety stock waiting time is simulated with the system dynamics approach, inventory policy has been put forward. [ABSTRACT FROM AUTHOR]