The Product Test Scheduling Problem

This research focused on product test scheduling in the presence of in-process and at-completion inspection constraints. Such testing arises in the context of the manufacture of products that must perform reliably in extreme environmental conditions. Often, these products must receive a certification from prescribed regulatory agencies at the successful completion of a predetermined series of tests. Operational efficiency is enhanced by determining the optimal order and start times of tests so as to minimize the makespan while ensuring that technicians are available when needed to complete in-process and at-completion inspections. We refer to this as the product test scheduling problem. We first formulated a mixed-integer linear programming (MILP) model to identify the optimal solution to this problem and solve it using a commercial optimization package. We also present a genetic algorithm (GA) solution methodology that is implemented and solved in Microsoft Excel. Computational results are presented demonstrating the merits and consistency of the MILP and GA solution approaches across a number of scenarios

The Developmental Test Scheduling Problem

Developmental testing of aircraft systems in the United States Air Force requires a complex set of resources for each test. The optimal scheduling of those resources is the job of the 412th Test Wing at Edwards Air Force Base. With more than 20 different Combined Task Forces requesting resources for roughly 300 flying missions each week, manual scheduling is a difficult task. The current process takes a team of schedulers several days to get a workable result from which they can start tailoring the final schedule. While concepts and techniques can be taken from industry scheduling problems, the body of knowledge as it relates to developmental test scheduling is sparse. The contribution of this paper is to initially document the Developmental Test Scheduling Problem, define it in structured terms for which a solution methodology can be designed, and present an Integer Programming based solution. The design allows for a scheduler to tailor an initial answer to fit nuanced and timely objectives and constraints. For this prototype effort the problem is scoped to the Iron Resources while bearing in mind the extensibility of the approach to Range Resources. This study and prototype will demonstrate results that will create an initial schedule in several hours and serve as a good starting point for the final schedule

Toyota production system

textBackground: There are various manufacturing methods and systems in automobile industries throughout the world. Of these, many practice lean manufacturing methods. The most effective and influential to all of these methods is the “Toyota Production System” (TPS). The TPS was invented by Toyota's founding fathers in 1930 in Japan. The TPS continuously evolves making it a benchmark for the manufacturing, product development or any other sector of industry. It is fully based on “Socio-Technical” systems in a continuously changing manufacturing environment. It is about learn through doing and also about tacit knowledge and not explicit procedural knowledge. Outcome: The Toyota Production System is called “The Toyota Way” and it actually gives you a roadmap or more of a compass to set your direction and helps you steer your own course. Toyota has internally developed simple but effective tools and consistently trains their team members to implement those in all aspects of manufacturing and designing their vehicle. For example, Toyota has developed Kaizen or continuous improvement through which they eliminate waste that adds cost without adding value no matter how small it is. Toyota is known for the quality of their products. Not surprisingly their product is made at a significantly lower price within a given segment of the auto market. It is a result of hard work, innovation, and a Japanese work culture of generations at Toyota all across the world. Conclusions: Through theoretical analysis backed by my personal observations as an employee and from the sales figures of Toyota automobiles, I firmly believe that Toyota backs up its philosophy of long term benefits over short term financial goals. The right processes will produce right results. It is also one of the top companies among their group of long term suppliers as Toyota challenges them and helps them to improve. Initial quality and customer satisfaction surveys of J.D.Powers and Associates for Toyota and Lexus vehicles have won numerous awards since 2001.Engineering Managemen

Optimization Models and Algorithms for Prototype Vehicle Test Scheduling

Automotive makers conduct a series of tests at pre-production phases of each new vehicle model development program. The main goal of those tests is to ensure that the vehicle models meet all design requirements by the time they reach the production phase. These tests target different vehicle components or functions, such as powertrain systems, electrical systems, safety aspects, etc. However, one big issue is that the cost of the resources, mainly prototype vehicles, invested in the testing process is exceedingly expensive. An individual prototype vehicle can cost over 5 times its counterpart’s price in the commercial market because many of the parts and the prototype vehicles themselves are highly customized and produced in small batches. Parts needed often require months of lead time, which constrains when vehicle builds can start. That, combined with inflexible time-window constraints for completing tests on those prototypes introduces significant time pressure, an unavoidable and challenging reality. What makes the problem even more difficult is that in addition to the prototype vehicle resources, there are other constrained supporting resources involved during the execution of those tests, such as testing facilities, instruments and equipment like cameras and sensors, human-power availability, etc. An efficient way to conquer the problem is to develop test plans with tight schedules that combine multiple tests on vehicles to fully utilize all available time while balancing the loads of other supporting resources. There are many challenges that need to be overcome in implementing this approach, including complex compatibility relationships between the tests and destructive nature of, e.g., crash tests. In this thesis, we show how to mathematically model these test scheduling problems as optimization problems. We develop corresponding solution approaches that enable quick generation of an efficient schedule to execute all tests while respecting all constraints. Our models and algorithms save test planners’ and engineers’ time, increase q their ability to quickly react to program changes, and save resources by ensuring maximal vehicle utilization.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137071/1/yuhuishi_1.pd

Technology transfer: Transportation

The application of NASA derived technology in solving problems related to highways, railroads, and other rapid systems is described. Additional areas/are identified where space technology may be utilized to meet requirements related to waterways, law enforcement agencies, and the trucking and recreational vehicle industries

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154104/1/kampfner1996.pd

Spartan Daily, February 15, 1955

Volume 42, Issue 88https://scholarworks.sjsu.edu/spartandaily/12138/thumbnail.jp