Testing strategies for k-out-of-n systems under forest type precedence constraints

This thesis investigates diagnosis strategies for k-out-of–n systems under precedence constraints. A k-out-of-n system consists of n independent components whose working probabilities of are known in advance. The system itself functions if at least k components function. The true state of the system is determined by the sequentially inspection of these components. This inspection is costly and the cost of inspection for each component is also known. This study aims to minimize expected cost of determining true state of such a system when there are forest type precedence constraints. Optimal inspection strategies are already known for series and parallel systems. In this study, modifications of these strategies are proposed for k-out-of-n systems. Numerical results are presented to evaluate and compare the proposed strategies

Testing strategies for k-out-of-n systems precedence constraints

This thesis investigates diagnosis strategies for k-out-of-n systems under the general type precedence constraints. Given the testing costs and the prior working probabilities, the problem is to devise strategies that minimizes the total expected cost of finding the correct state of the system. The true state of the system is determined by sequential inspection of these n components. We try to find good strategies for the problem under general type precedence constraints by adapting an optimal algorithm that works when there are no precedence constraints. We refer to this algorithm Intersection-Precedence and represent the strategy that we obtain efficiently by a Block-Walking Diagram structure. Since no computational results are reported in the literature for this particular problem, in order to benchmark the performance of the Intersection-Precedence algorithm, we develop Tabu Search and Simulated Annealing algorithms that find permutation strategies.We conduct an extensive computational study to compare the results obtained by the alternative algorithms and we observe that Intersection- Precedence algorithm, in general, outperforms the other algorithms

Project scheduling with modular project completion on a bottleneck resource.

In this paper, we model a research-and-development project as consisting of several modules, with each module containing one or more activities. We examine how to schedule the activities of such a project in order to maximize the expected profit when the activities have a probability of failure and when an activity’s failure can cause its module and thereby the overall project to fail. A module succeeds when at least one of its constituent activities is successfully executed. All activities are scheduled on a scarce resource that is modeled as a single machine. We describe various policy classes, establish the relationship between the classes, develop exact algorithms to optimize over two different classes (one dynamic program and one branch-and-bound algorithm), and examine the computational performance of the algorithms on two randomly generated instance sets.Scheduling; Uncertainty; Research and development; Activity failures; Modular precedence network;

A Review of System Development Systems

The requirements for a system development system are defined and used as guidelines to review six such systems: SAMM, SREM, SADT, ADS / SODA, PSL/PSA and Systematics. It is found that current system development systems emphasise only validation and user verification. They can perform relatively little on automatic file optimisation, process optimisation and maintenance.postprin

Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

Scheduling and shop floor control in commercial airplane manufacturing

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.Includes bibliographical references (p. 73-75).Boeing is the premier manufacturer of commercial jetliners and a leader in defense and space systems. Competition in commercial aircraft production is increasing and in order to retain their competitive position, Boeing must strive to improve their operations by reducing costs. Boeing factories today still schedule and monitor the shop floor much as they have for the past 100 years. This thesis compares and contrasts several different methods for shop floor control and scheduling including Boeing's barcharts, Toyota production system, critical chain, and dynamic scheduling. Each system is will be analyzed with respect to how it handles variability in labor output required and how that affects which products are typically made under each system. In additional to qualitative comparisons, discrete event simulations comparing the various strategies will be presented. Areas for future simulation study are also discussed. The recommended approach for commercial airplane assembly is critical chain. A suggested implementation plan is presented along with methods to ease acceptance.by Vikram Neal Sahney.S.M.M.B.A

Risk-Based Optimal Scheduling for the Predictive Maintenance of Railway Infrastructure

In this thesis a risk-based decision support system to schedule the predictive maintenance activities, is proposed. The model deals with the maintenance planning of a railway infrastructure in which the due-dates are defined via failure risk analysis.The novelty of the approach consists of the risk concept introduction in railway maintenance scheduling, according to ISO 55000 guidelines, thus implying that the maintenance priorities are based on asset criticality, determined taking into account the relevant failure probability, related to asset degradation conditions, and the consequent damages

A condition-based maintenance policy for multi-component systems with a high maintenance setup cost

Condition-based maintenance (CBM) is becoming increasingly important due to the development of advanced sensor and ICT technology, so that the condition data can be collected remotely. We propose a new CBM policy for multi-component systems with continuous stochastic deteriorations. To reduce the high setup cost of maintenance, a joint maintenance interval is proposed. With the joint maintenance interval and control limits of components as decision variables, we develop a model for the minimization of the average long-run maintenance cost rate of the systems. Moreover, a numerical study on a case of a wind power farm consisting of a large number of non-identical components is performed, including a sensitivity analysis. At last, our policy is compared to a corrective-maintenance-only policy

Sequential testing of series parallel systems

In this thesis, we study the sequential testing problem of 3-level deep Series Parallel systems (SPS). We assess the performance of depth-first permutation (DFP) algorithm that has been proposed in the literature. DFP is optimal for 1-level deep, 2-level deep SPSs and 3-level deep SPSs that consist of identical components. It can be used to test general SPSs. We report the first computational results regarding the performance of DFP for 3-level deep SPSs by comparing its performance with a dynamic version of DFP and a hybrid simulated annealing-tabu search algorithm that we developed. In order to implement the algorithms, we propose an efficient method to compute the expected cost of a permutation strategy. The results of computational experiments for this algorithm and other algorithms proposed in the literature are reported