A current trend in residential construction is the use of prefabricated wall panels. It is important to carefully establish how panels will be stacked, because an optimal sequence will improve productivity and reduce the possibility of worker injury. Mathematical models and heuristics are proposed for solving the panel stacking problem without consideration of interference. Dissertation work includes a mathematical model of the corresponding panel stacking problems in which the goal is to minimize total weighted panel move distance concurrent with certain construction assumptions. The heuristic method was provided to establish how each panel would be stacked and gave the drop-off location of each stack. The heuristic method was found to be able to reduce the total weighted panel move distance and ensure connectivity was always maintained, meanwhile, interference could also be avoided. In terms of solution speed, the heuristic method can solve real size problems in less than one second. Solutions to such problems can increase productivity. Three improvements to the only known existing panel stacking algorithm with consideration of interference were proposed. The computational results indicate the proposed algorithm performed better than existing algorithm in all experimental cases. Improvement on panel move distance ranged from 1.35-47.93%, and improvement on interfering panels ranged from 20-100%. The proposed algorithm can solve non-rectangular cases (not possible with existing algorithm) and was compared with an experienced panel designer and commercial software. When compared to the proposed algorithm, total weighted panel move distance increased 0.10-85.52% and 0.77-136.23%, respectively, for the panel designer and software. While connectivity was 100% for all cases with the proposed algorithm (the algorithm ensures connectivity is always maintained), it ranged from 69.56-86.95% and 73.33-90.91%, however, for the panel designer and software respectively. Finally, the proposed algorithm can solve the interfering panels in the last stack: this cannot be done with the existing algorithm. Because prefabricated wall panels are typically large and cumbersome to work with, there is a significant probability of worker injury. It is important to carefully establish how each panel will be handled by workers. This is typically the responsibility of field construction foreman, but such personnel are often ill-equipped to make such decisions. An alternative, proactive approach is to establish how each panel will be handled in advance, such that overall ergonomic consequences can be properly considered. This dissertation presents mathematical models of the corresponding construction task scheduling and worker assignment problems, where the goal is to minimize total project completion time (subject to worker quantity constraints) and assign tasks to workers as evenly as possible. The solution of such problems can help residential construction managers better plan construction by establishing the ergonomic impact associated with a given construction plan. A heuristic was also developed to solve large problems by balancing workload between workers. The heuristic was found to be able to provide near-optimal solutions, and can solve large problems in less than one second. / Ph. D.

Lean production prescribes training workers on all tasks within the cell to adapt to changes in customer demand. Multi-skilling of workers can be achieved by cross-training. Cross-training can be improved and reinforced by implementing job rotation. Lean production also prescribes using job rotation to improve worker flexibility, worker satisfaction, and to increase worker knowledge in how their work affects the rest of the cell. Currently, there is minimal research on how to assign multi-skilled workers to tasks within a lean production cell while considering multi-skilling and job rotation. In this research, a new mathematical model was developed that assigns workers to tasks, while ensuring job rotation, and determines the levels of skill, and thus training, necessary to meet customer demand, quality requirements, and training objectives. The model is solved using sequential goal programming to incorporate three objectives: overproduction, cost of poor quality, and cost of training. The results of the model include an assignment of workers to tasks, a determination of the training necessary for the workers, and a job rotation schedule. To evaluate the results on a cost basis, the costs associated with overproduction, defects, and training were used to calculate the net present cost for one year. The solutions from the model were further analyzed using a simulation model of the cell to determine the impact of job rotation and multi-skilling levels on production line performance. The measures of performance include average flowtime, work-in-process (WIP) level, and monthly shipments (number produced). Using the model, the impact of alternative levels of multi-skilling and job rotation on the performance of cellular manufacturing systems is investigated. Understanding the effect of multi-skilling and job rotation can aid both production managers and human resources managers in determining which workers need training and how often workers should be rotated to improve the performance of the cell. The lean production literature prescribes training workers on all tasks within a cell and developing a rotation schedule to reinforce the cross-training. Four levels of multi-skilling and three levels of job rotation frequency are evaluated for both a hypothetical cell and a case application in a relatively mature actual production cell. The results of this investigation provide insight on how multi-skilling and job rotation frequency influence production line performance and provide guidance on training policies. The results show that there is an interaction effect between multi-skilling and job rotation for flowtime, work-in-process, in both the hypothetical cell and the case application and monthly shipments in the case application. Therefore, the effect of job rotation on performance measures is not the same at all levels of multi-skilling thus indicating that inferences about the effect of changing multi-skilling, for example, should not be made without considering the job rotation level. The results also indicate that the net present cost is heavily influenced by the cost of poor quality. The results for the case application indicated that the maturity level of the cell influences the benefits derived from increased multi-skilling and affects several key characteristics of the cell. As a cell becomes more mature, it is expected that the quality levels increase and that the skill levels on tasks normally performed increase. Because workers in the case application already have a high skill level on some tasks, the return on training is not as significant. Additionally, the mature cell has relatively high quality levels from the beginning and any improvements in quality would be in small increments rather than in large breakthroughs. The primary contribution of this research is the development of a sequential goal programming worker assignment model that addresses overproduction, poor quality, cross-training, and job rotation in order to meet the prescription in the lean production literature of only producing to customer demand while utilizing multi-skilled workers. Further contributions are analysis of how multi-skilling level and job rotation frequency impact the performance of the cell. Lastly, a contribution is the application of optimization and simulation methods for comprehensively analyzing the impact of worker assignment on performance measures. / Ph. D.