Nilgun Fescioglu-Unver

Continuous improvement in industrial processes has made efficient internal material transportation critical. This study presents a decision support system for tracking internal transportation vehicles and providing effective inner logistics management. The proposed model includes a barcoding based transportation vehicle tracking system, a forecasting model for daily transportation demands of different buildings and presents a predictive demand-vehicle assignment mathematical model. Results show that the model reduces the operational costs due to vehicle search and vehicle transportation, and material damage costs due to vehicle-material mismatch at a great extent.

The ceramic sanitaryware production process consists of casting, drying, glazing, and firing operations. The operation that uses the most energy is the firing process. This study handles a case sanitaryware production factory and proposes a production planning method for energy-efficient manufacturing. In the case factory, the firing process takes place on wagons that carry the products through a tunnel-gas oven. Increasing the wagon surface area utilization decreases the energy consumption per unit product. The wagons continuously move with a predetermined speed and pick up their loads from the end of the glazing lines. The glazing lines have limited-sized end buffers, and products are manually carried in case of a buffer overflow. A wagon can load a product only if the product is ready in the glazing line end buffer while the wagon is passing in front of that line in real-time. Efficient wagon loading requires having the right products at the end buffers at the right time. This study develops a hybrid simulation optimization model to determine the production plan that minimizes the number of wagons used and the buffer overflows. The proposed method consists of two parts. The first part uses a linear programming model to assign the product demands to appropriate glazing lines such that the glazing lines' workload is balanced in terms of total production time and total product surface in lines. Then the model orders the products in each line according to their types and assigns them to drying process vehicles. The second part of the model uses a hybrid simulation-genetic algorithm heuristic to obtain the best product/wagon assignments with the given glazing production plan. The production plan is further improved with a heuristic drying vehicle replacement rule. The model gradually improves the production plan within a closedloop cycle between the wagon-product assignment heuristic and the drying vehicle replacement heuristic. Results show that the model can effectively reduce the number of wagons used and buffer overflow for a given demand.

Optimal planning of resources with daily/real time resource management is important for obtaining the most benefit from microgrids. There exist several mathematical models and heuristic rule based policies for microgrid resource management. Mathematical models provide optimal results, while heuristic policies are simple to implement but cannot guarantee optimality. Although both models are used in the literature, studies do not analyze the benefits of using mathematical models over heuristic rule based ones. This study proposes a mixed integer programming based mathematical model and a rule based model and compares their performances for a newly established microgrid at Turkey. Both models aim to minimize the daily cost of the microgrid by planning the use, sale, and storage of the energy obtained from the renewable resources. The results quantify the benefits of using the mathematical model over the rule based model for the case microgrid under different conditions. The analysis shows that the difference between the models' performances changes according to the energy pricing policy and seasons. Under certain conditions, the simple rule based policy can provide close to optimal results.

BACKGROUND: Each year, hospitals lose a considerable amount of time and money due to misplaced mobile assets. In addition the assets which remain in departments that frequently use them depreciate early, while other assets of the same type in differe