With the ongoing technology battles and price wars in today's competitive economy, every company is looking for an advantage over its peers. A particular choice of facility layout can have a significant impact on the ability of a company to maintain lower operational expenses under uncertain economic conditions. It is known that systems with less congestion have lower operational costs. Traditionally, manufacturing facility layout problem methods aim at minimizing the total distance traveled, the material handling cost, or the time in the system (based on distance traveled at a specific speed). The proposed methodology solves the looped layout design problem for a looped layout manufacturing facility with a looped conveyor material handling system with shortcuts using a system performance metric, i.e. the work in process (WIP) on the conveyor and at the input stations to the conveyor, as a factor in the minimizing function for the facility layout optimization problem which is solved heuristically using a permutation genetic algorithm. The proposed methodology also presents the case for determining the shortcut locations across the conveyor simultaneously (while determining the layout of the stations around the loop) versus the traditional method which determines the shortcuts sequentially (after the layout of the stations has been determined). The proposed methodology also presents an analytical estimate for the work in process at the input stations to the closed looped conveyor. It is contended that the proposed methodology (using the WIP as a factor in the minimizing function for the facility layout while simultaneously solving for the shortcuts) will yield a facility layout which is less congested than a facility layout generated by the traditional methods (using the total distance traveled as a factor of the minimizing function for the facility layout while sequentially solving for the shortcuts). The proposed methodology is tested on a virtual 300mm Semiconductor Wafer Fabrication Facility with a looped conveyor material handling system with shortcuts. The results show that the facility layouts generated by the proposed methodology have significantly less congestion than facility layouts generated by traditional methods. The validation of the developed analytical estimate of the work in process at the input stations reveals that the proposed methodology works extremely well for systems with Markovian Arrival Processes.

This research investigates the problem of constrained sequencing of a set of jobs on a conveyor system with the objective of minimizing setup cost. A setup cost is associated with extra material, labor, or energy required due to the change of attributes in consecutive jobs at processing stations. A finite set of attributes is considered in this research. Sequencing is constrained by the availability of two elements ??orage buffers and conveyor junctions. The problem is motivated by the paint purge reduction problem at a major U.S. automotive manufacturer. First, a diverging junction with a sequence-independent setup cost and predefined attributes is modeled as an assignment problem and this model is extended by relaxing the initial assumptions in various ways. We also model the constrained sequencing problem with an off-line buffer and develop heuristics for efficiently getting a good quality solution by exploiting the special problem structure. Finally, we conduct sensitivity analysis using numerical experiments, explain the case study, and discuss the use of the simulation model as a supplementary tool for analyzing the constrained sequencing problem.

The design and operation of a high volume conveyor sortation system are important due to its high cost, large footprint and critical role in the system. In this thesis, we study the characteristics of the conveyor sortation system from performance evaluation and design perspectives employing continuous modeling approaches. We present two continuous conveyor models (Delay and Stock Model and Batch on Conveyor Model) with different representation accuracy in a unified mathematical framework. Based on the Batch on Conveyor Model, we develop a fast fluid simulation methodology. We address the feasibility of implementing fluid simulation from modeling capabilities, algorithm design and simulation performance in terms of accuracy and simulation time. From a design perspective, we focus on rates determination and accumulation design in the accumulation and merge subsystem. The optimization problem is to find a minimum cost design that satisfies some predefined performance requirements under stochastic conditions. We first transform this stochastic programming problem into a deterministic nonlinear programming problem through sample path based optimization method. A gradient based method is adopted to solve the deterministic problem. Since there is no closed form for performance metric even for a deterministic input stream, we adopt continuous modeling to develop deterministic performance evaluation models and conduct sensitivity analysis on these models. We explore the prospects of using the two continuous conveyor models we presented.

This thesis is motivated by practical problems encountered in handling live products in the poultry processing industry, where live birds are manually transferred by human labors. As the task of handling live products is often unpleasant and hazardous, it is an ideal candidate for automation. To reduce the number of configurations and live birds to be tested, this thesis focuses on developing analytical models based on the Lagrange method to predict the effect of mechanical inversion on the shackled bird. Unlike prior research which focused on the effect of different inversion paths on the joint force/torque of a free-falling shackled bird, this thesis research examines the effect of kinematic constraints (designed to support the bird body) on the shackled bird. Unlike free-falling, the imposed kinematic constraints enable the shackled bird to rotate about its center of mass, and thus minimize wing flapping. In this thesis, birds are geometrically approximated as ellipsoids while the lower extremity is modeled as a pair of multi-joint serial manipulators. With the constraint equations formulated into a set of differential algebraic equations, the equations of motion as well as Lagrange multipliers characterizing kinematical constraints are numerically solved for the bird motion, specifically the position, velocity, and orientation and hence the forces and torques of the joints. The dynamic models are verified by comparing simulation results against those obtained using a finite element method. The outcomes of this thesis will provide some intuitive insights essential to design optimization of a live-bird transfer system.