Life-cycle of fatigue sensitive structures under uncertainty

Fatigue is the one of the main contributors to problems related to structural safety of civil and marine structures. Life-cycle management (LCM) techniques considering various uncertainties can be used to predict the safe service life of fatigue sensitive structures, plan for their future inspections and support the decision making process regarding maintenance and repair actions. This paper provides a brief overview of the LCM of fatigue sensitive civil and marine structures under uncertainty. Probabilistic performance prediction, inspection scheduling and maintenance optimization for such structures are discussed

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Development of the Integrated Model of the Automotive Product Quality Assessment

Issues on building an integrated model of the automotive product quality assessment are studied herein basing on widely applicable methods and models of the quality assessment. A conceptual model of the automotive product quality system meeting customer requirements has been developed. Typical characteristics of modern industrial production are an increase in the production dynamism that determines the product properties; a continuous increase in the volume of information required for decision-making, an increased role of knowledge and high technologies implementing absolutely new scientific and technical ideas. To solve the problem of increasing the automotive product quality, a conceptual structural and hierarchical model is offered to ensure its quality as a closed system with feedback between the regulatory, manufacturing, and information modules, responsible for formation of the product quality at all stages of its life cycle. The three module model of the system of the industrial product quality assurance is considered to be universal and to give the opportunity to explore processes of any complexity while solving theoretical and practical problems of the quality assessment and prediction for products for various purposes, including automotive

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case

Ant colony system-based applications to electrical distribution system optimization

Chapter 16, February 201

A Review of Trip Planning Systems.

This report reviews current information provision in all modes of transport and assesses the needs for and benefits of trip planning systems. The feasibility of trip planning systems is discussed given the current state of technology and information availability and supply. The review was stimulated by technological developments in telecommunications and information technology which are providing the possibility of a greatly enhanced quality of information to aid trip planning decisions. Amongst the conclusions reached were the following: Current information provision is considered deficient in many respects. Travellers are often unaware of alternative routes or services and many are unable to acquire adequate information from one source especially for multi-modal journeys. In addition, there is a lack of providing real time information where it is required (bus stops and train stations) and of effective interaction of static and real time information. Most of the projects, which integrate static and dynamic data, are single mode systems. Therefore there is a need for an integrated trip planning system which can inform and guide on all aspects of transport. Trip planning systems can provide assistance in trip planning (before and during the journey) using one or a number of modes of travel, taking into account travellers preferences and constraints, and effectively integrating static and dynamic data. Trip planning systems could adversely affect traffic demand as people who become aware of new opportunities might be encouraged to make more journeys. It could also affect travellers choice as a result of over-saturation of information, over-reaction to predictive information, and concentration on the same 'best' routes. However, it can be argued, based on existing evidence, that such a system can benefit travellers, and transport operators as well as the public sector responsible for executing transport policies. Travellers can benefit by obtaining adequate information to help them in making optimal decisions and reducing uncertainty and stress associated with travel. Public transport operators can benefit by making their services known to customers, leading to increased patronage. Public transport authorities can use the supply of information to execute their transport policies and exercise more control over traffic management

Advancing High-Speed Rail Policy in the United States, Research Report 11-18

This report builds on a review of international experience with high-speed rail projects to develop recommendations for a High-speed rail policy framework for the United States. The international review looked at the experience of Korea, Taiwan, China, and several countries in Europe. Countries in Asia and Europe have pursued high-speed rail (HSR) to achieve various goals, which include relieving congestion on highway networks, freeing up capacity on rail network for freight train operations, and reducing travel time for travelers. Some of the key rationales do not work well in the US context. As an example, in the US, freight companies own most of the rail network and, hence, do not need government intervention to free up capacity for their operations. We concluded the potential to reduce travel times coupled with improved travel time reliability and safety will be the strongest selling points for HSR in the US. HSR lines work best in high-density, economically active corridors. Given that there are a limited number of such corridors in the US, our study recommends the US HSR project funding mix be skewed heavily toward state bonds guaranteed by the federal government. This will ensure that the states that benefit directly from the projects pay most of the costs, making it more palatable to states that may not have HSR projects. For the projects that span multiple states, member states may have to negotiate the level of financial responsibility they will bear, and this will require detailed negotiations and financial setups that are not addressed in this report. Other measures the federal government needs to put in place include designating a key agency and dedicated funding source, and developing regulations and specifications for HSR design and construction. States that embark on HSR projects should start with formal legislation and put in place structures to ensure sustained political support throughout the planning and construction of the project. The federal government also needs to move quickly to foster educational and training centers to build up the HSR workforce in the country