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Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Today companies continue to examine their costs in business life where competition is hard. In this sense, warehouse site selection, which is significantin terms of logistics costs, becomes a critical process. Warehouse site selection decision making model proposed in this study is developed for contributing the efffiency of distribution network and minimizing logistics costs. In this study, to solve warehouse site selection problem 3 different methods are synthesised, which are Analytical Hierarchy Process (AHP), Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and with Multi- Objective Optimization by Ratio Analysis (MOORA). AHP method is used for determining the criteria of alternatives and VIKOR and MOORA methods are used for ranking of alternatives.Using real data instead of classical pairwise comparison scales for AHP and VIKOR applications and the use of MOORA method in warehouse site selection problem have been important for considering a new approach and solution method in this field. The application is carried out for the decision problem of determining 3 best alternatives of a casting factory among 11 alternatives. In the study, comparisons are conducted for results of both of the methods and final decision is made according to application results. [ABSTRACT FROM AUTHOR]

In this paper a solution method is proposed for emphasizing the importance of costumer needs at the starting of Quality Function Deployment (QFD) application when there are multi costumer groups. Data Envelopment Analysis (DEA) steps are added to an algorithm in which an Analytic Network Process (ANP) approach is used in QFD. The need for adding DEA steps is determining the efficient customer requirements when there are multi customer groups. This solution approach is called DEANP which aggregates data DEA to ANP. The relative importance values of product technical requirements are calculated with this algorithm and application is performed at a manufacturer of white goods company in Turkey. The fact that using DEANP instead of ANP produced more powerful solutions is also confirmed by marketing specialists. [ABSTRACT FROM AUTHOR]

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]