Industrial Engineering

The design of production and service systems includes deciding on the product/service family to be produced, long-term demand forecasting, determining the materials, processes, and methods to be used, selecting machinery and equipment, and designing workflow, work systems, and facility layout. The planning problem involves forecasting incoming jobs or orders in an existing production or service system, prioritizing them, matching capacity with demand through capacity planning, and determining which jobs or orders will be processed, when, and in what quantities by existing production units.

Related Projects:

• Green Robotic Cell Scheduling, TÜBİTAK-1001, 2016–2018, Budget: 243,750 TL
• Control of the Ministry of National Education Budget and Monitoring Performance-Based School Education Performance, KAMAG Project, Ministry of National Education, 2009–2012, Budget: 1,400,000 TL
• Maximization of Production Rate in Flexible Flow Shop Systems: The Value of Flexibility, Mathematical Modeling and Solution Techniques, TÜBİTAK, 2011–2013, Budget: 121,530 TL
• Software Development Based on Mathematical Models for the Optimization of Safety Stocks and Order Lot Sizes, KOSGEB, 2011–2012, Budget: 158,400 TL

Supply chain and logistics management is becoming increasingly important for gaining competitive advantage in a globalizing market. In this context, the use of analytical methods for the planning, design, and control of supply chain and logistics systems is gaining importance.

Related Projects:

• Route planning and cost allocation optimization in full truckload shipper collaboration, TÜBİTAK, 2012–2015, Budget: 168,860 TL
• Facility location and capacitated intermodal hub network design for main distribution centers, TÜBİTAK, 2012–2014, Budget: 139,970 TL

Many real-life problems can be formulated in this way and are successfully applied in numerous fields such as production, supply chain, logistics, engineering design, and finance. It requires an interdisciplinary approach and background that integrate multiple disciplines, including mathematics, computer science, and management science. The fundamental solution techniques include mathematical modeling and heuristic methods.

Related Projects:

• Energy-Efficient Wireless Sensor Network Design with Topology Control and Partial Redundancy-Based Reliability Measures, TÜBİTAK, 2013–2016, Budget: 84,000 TL

It is used in modeling and solving engineering problems involving uncertainty in the production and service sectors, and it can also be applied to economic, healthcare, public administration, and business problems where similar dynamics arise. The field of decision analysis examines individuals’ behavior in single- and multi-criteria decision problems, both by developing analytical models and through behavioral analysis.

Related Projects:

• Asymptotic Properties of Complex Stochastic Systems, TÜBİTAK, 2011–2014, Budget: 82,380 TL
• Analysis of the Value of Information and Risk Sensitivity Using Different Approaches, TÜBİTAK, 2011–2012, Budget: 12,000 TL

The difference between the Soft Computing approach and traditional computing methods is that it increases the robustness and manageability of solutions by tolerating uncertainty, partial correctness, and imprecision. Soft computing takes the operating principles of the human brain as its role model.

Related Projects:

• Type-1 and Full Type-2 Fuzzy System Models, NSERC (National Science and Engineering Research Council) – Discovery Grant, Canada, Year: 2011–2015, Budget: 300,000 TL