Musculoskeletal disorders (MSDs) have become a major health concern with the industrial revolution and technological advances. The National Institute for Occupational Safety and Health (NIOSH) recently estimated the cost of MSDs at $13 to $20 billion annually. Back, spine, and spinal cord disorders add up to 60% of the total MSD injuries. Based on pervious studies, it is known that lumbar ligaments play a limited or little role in stabilizing the spine; where as the musculature around the spine is the major stabilizing structure. However, repetitive or prolonged static displacement or load induces creep in passive tissues of the spine including ligaments, disc, and joint capsule. The resulting creep in the ligaments or the laxity developed in the viscoelastic structure causes instability of the spine associated with pain, leaving the spine without protection. This study concentrates on the response of the lumbar spine when subjected to static loading. Twenty-two in vivo feline preparations were subjected to four different intensities of load, and electrical activity of the multifidus muscles for six lumbar levels and creep behavior of the supraspinous ligament were observed for twenty minutes of loading and seven hours of rest period. Results show that seven hours of rest period was not enough for the multifidus activity and creep developed in the viscoelastic tissue to return to normal. Larger loads elicited larger initial vertical displacement in the lumbar spine as well as higher creep values. Based on the observed data, four exponential and time dependant models were developed in the mathematical description of the electrical activity and the vertical displacement in the supraspinous ligament for both loading and recovery periods.

An assembly line that procures raw materials from outside suppliers and processes the materials into finished products is considered in this research. An ordering policy is proposed for raw materials to meet the requirement of a production facility, which, in turn, must deliver finish products in a fixed quantity at a fixed time interval to the outside buyers. Two different types of raw materials, unfinished and ready-to-use, are procured for the manufacturing system. The unfinished raw materials are turned into processed raw materials after preprocessing. In the assembly line, the processed raw materials and the ready raw materials are assembled to convert into the final products. A cost model is developed to aggregate the total costs of raw materials, Work-in-process, and finished goods inventory. Based on the product design and manufacturing requirement a relationship is established between the raw materials and the finished products at different stages of production. A non-linear integer-programming model is developed to determine the optimal ordering policies for procurement of raw materials, and shipment of assembly product, which ultimately minimize the total costs of the model. Numerical examples are presented to demonstrate the solution technique. Sensitivity analysis is performed to show the effects of the parameters on the total cost model. Future research direction is suggested for further improvement of the existing results.

In an imperfect manufacturing process, the defective items are produced with finished goods. Rework process is necessary to convert those defectives into finished goods. As the system is not perfect, some scrap is produced during this process of rework. In this research, inventory models for a single-stage production process are developed where defective items are produced and reworked, where scrap is produced, detected and discarded during the rework. Two policies of rework processes are considered (a) First policy: rework is done within the cycle, and (b) Second policy: rework is done after N cycles of normal production. Also, three types of scrap production and detection methods are considered for each policy, such as (i) scrap is detected before rework, (ii) scrap is detected during rework and (iii) scrap is detected after rework. Based on these inventory situations, the total cost functions for a single-stage imperfect manufacturing system are developed to find the optimum operational policy. Some numerical examples are provided to validate the model and a sensitivity analysis is carried out with respect to different parameters used to develop the model.

This research focuses on supporting the formation of strategic alliances through the concept of cooperative commerce, where suppliers and buyers work together to jointly optimize their businesses. The general goal of this research is to examine existing cooperative commerce models for obstacles that would hinder their successful implementation into modern industrial applications and to address those shortcomings. Total annual cost equations are formulated to capture the joint total relevant cost of cooperative commerce business relationships. These total joint relevant cost models will include terms that capture the ordering cost, holding cost, and cost of quality, as well as any applicable investment cost for process improvements, consistent with traditional economic order quantity and economic production quantity theory. This research corrects a modeling error of Affisco, et al. (2002) that led to underestimating the effectiveness of process improvements in joint economic lot size models. In addition, the models are expanded to accommodate a full range of product quality inspection policies, from zero to one hundred percent product inspections. Furthermore, the models are modified to account for the cost of scrap generation, as well as the effects of accepting non-conforming product and rejecting conforming product during quality inspections. Once the total cost models are expanded to account for these neglected costs, the joint total relevant cost equations are minimized to find the optimal batch sizes, and the effects of each model extension on the model solution are studied. Results indicate that these extensions do have a significant impact on the model results, such as reduced optimal batch sizes and increased optimal fraction conforming product.

In this study, the machining performance of a series of commercially available coated tungsten based cemented carbides, with 55o diamond shape, were investigated during finish turning of AISI 1018 steel under dry conditions. The inserts tested had a coating of TiN, Al2O3, TiN/Al2O3 and TiC/Al2O3/TiN respectively. For comparison, uncoated cemented tungsten carbide was also tested under the same cutting conditions. The coated tools exhibited superior wear resistance over the uncoated tool. The TiC/Al2O3/TiN coated tool had the lowest flank wear due to the high abrasive resistance of the TiC layer. The Al2O3 coated tool showed superior wear-resistance over the TiN/Al2O3 coated tool due to the TiN coating that deteriorated the effect of the Al2O3 outer layer. The TiN coated tool showed the least wear resistance with respect to the other coated tools. Surface roughness appeared to increase with flank wear while oscillating for all the tested tools except for the TiN coated tool. The TiN coated tool produced a relatively consistent surface roughness that was not significantly affected by the flank wear under the conditions tested. The coated tools produced lower surface roughness compared to the uncoated tool, except for the TiN/Al2O3 coated tool, which produced considerably higher surface roughness. The reason for this however was the geometry of the chip breaker, rather than the coating materials, which produced longer chips that came in contact with the work piece during the machining process. The TiC/Al2O3/TiN coated tool produced the lowest surface roughness of all the tools tested.

Automated guided vehicles (AGVs) are widely used in container terminals for the movement of material from shipping to the yard area and vice versa. Research in this area is directed toward the development of a path layout design and routing algorithms for container movement. The problem is to design a path layout and a routing algorithm that will route the AGVs along the bi-directional path so that the distance traveled will be minimized. This thesis presents a bi-directional path flow layout and a routing algorithm that guarantee conflict-free, shortest time routes for AGVs. Based on the path layout, a routing algorithm and sufficient, but necessary conditions, mathematical relationships are developed among certain key parameters of vehicle and path. A high degree of concurrency is achieved in the vehicle movement. The routing efficiency is analyzed in terms of the distance traveled and the time required for AGVs to complete all pickup and drop-off jobs. Numerical results are presented to compare performance of the proposed model. The research provides the foundation for a bi-directional path layout design and routing algorithms that will aid the designer to develop complicated path layouts.

Reports for adult population indicate that almost 80% of the adult population has reported some form of lower back aches. Each year American workers suffer more than 300,000 lost-time injuries involving musculoskeletal disorders of the back, with the costs that run into billions of dollars. Sedentary tasks are known to be major contributing factors of back pain. Prior studies have indicated that the myoelectric activity of the lumbar region decreases when the back rest inclination of a seat increased. An increase in seat pan inclination so that it increases pressure on the leg muscles is also a cause for back pain. Seating posture is also known to be a leading cause of back pain. This study focuses on the response of the latissimus dorsi muscle in the trunk, to the backrest and seat angle inclinations for different seating postures. Twenty one participants took part in the backrest experiment. The automobile seat backrest angle was varied for two angles of 90 and 100 degrees in a one hour driving session. Ten participants took part in the seat angle experiment; the seat was set at 0 and 10 degrees for a 30 minutes session at each angle. The muscle activity of the latissimus dorsi was recorded for seating postures at each angle. Based on the electromyography data, the results of analyses of variance for mean of root mean square values for the backrest experiment (P < 0.05) showed significant change. In seat angle experiment the analysis of variation of the mean values for root mean square values at (P < 0.05) was significant. It is concluded that increased backrest and inclined seat angle decreases muscle activity in the latissimus dorsi muscle.

Transportation costs constitute up to thirty percent of the total costs involved in a supply chain. Outsourcing the transportation service requirements to third party logistics providers have been widely adopted, as they are economically more rational than owning and operating a service. Transportation service procurement has been traditionally done through an auctioning process where the auctioneer (shipper) auctions lanes (distinct delivery routes) to bidders (carriers). Individual lanes were being auctioned separately disallowing the carriers to express complements and substitutes. Using combinatorial auctions mechanism to auction all available lanes together would allow the carriers to take advantage of the lane bundles, their existing service schedule, probability of securing other lanes and available capacity to offer services at lower rates and be more competitive. The winners of the auction are the set of non-overlapping bids that minimize the cost for the shippers. The winner determination problem to be solved in determining the optimal allocation of the services in such kind of combinatorial auctions is a NP-hard problem. Many heuristics like approximate linear programming, stochastic local search have proposed to find an approximate solution to the problem in a reasonable amount of time. Akcoglu et al [22] developed the opportunity cost algorithm using the local ratio technique to compute a greedy solution to the problem. A recalculation modification to the opportunity cost algorithm has been formulated where opportunity costs are recalculated every time for the set of remaining bids after eliminating the bid chosen to be a part of the winning solution and its conflicts have eliminated. Another method that formulates the winning solution based on the maximum total revenue values calculated for each bid using the opportunity cost algorithm has also been researched.

The omnipresence of software has forced upon the industry to produce efficient software in a short time. These requirements can be met by code reusability and software testing. Code reusability is achieved by developing software as components/modules rather than a single block. Software coding teams are becoming large to satiate the need of massive requirements. Large teams could work easily if software is developed in a modular fashion. It would be pointless to have software that would crash often. Testing makes the software more reliable. Modularity and reliability is the need of the day. Testing is usually carried out using test cases that target a class of software faults or a specific module. Usage of different test cases has an idiosyncratic effect on the reliability of the software system. Proposed research develops a model to determine the optimal test case policy selection that considers a modular software system with specific test cases in a stipulated testing time. The proposed model, models the failure behavior of each component using a conditional NHPP (Non-homogeneous Poisson process) and the interactions of the components by a CTMC (continuous time Markov chain). The initial number of bugs and the bug detection rate are known distributions. Dynamic programming is used as a tool in determining the optimal test case policy. The complete model is simulated using Matlab. The Markov decision process is computationally intensive but the implementation of the algorithm is meticulously optimized to eliminate repeat calculations. This has saved roughly 25-40% in processing time for different variations of the problem.

Risk management involves assessing the risk sources and designing strategies and procedures to mitigate those risks to an acceptable level. Measurement of risk factors plays an important role in the assessment of risk. This research proposes to develop risk assessment frameworks and mathematical model (Probabilistic Risk Assessment model) identify the risk factors. Quantification and prioritization of risk factors will help to design controls, resource allocation policies and minimize the total cost using the Cost Minimization model. The proposed models are applied to a complex system that is representative of actual business situations.