A survey of AI in operations management from 2005 to 2009

Purpose: the use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the ten-year period 1995-2004. Like the previous survey, it uses Elsevier’s Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case-based reasoning (CBR), fuzzy logic (FL), knowledge-Based systems (KBS), data mining, and hybrid AI in the four application areas are identified. Findings: the survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004 (Kobbacy et al. 2007). Like the previous survey, it uses the Elsevier’s ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings: The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research

Bargaining power, ownership and control of international joint ventures in Taiwan

This thesis provides an empirical analysis of international joint venture activities in Taiwan. The primary purpose is to examine control and its antecedents in terms of ownership, bargaining power, resources contribution, and motivation for forming international joint ventures. Primary data collected by a mail questionnaire is analysed along five core dimensions of international joint venture activities. First, the mechanism, focus, and extent of parent control is identified and tested in a number of sample characteristics. These empirical results also reveal that most joint ventures in Taiwan have higher autonomy and have more autonomy on the appointment of key function managers. Parent firms seek to focus their control over specific activities of the joint ventures rather than attempting to control the entire range of joint venture activities. Second, the results of equity shares held by the host country parents and foreign parents show that both parents have minority shareholding in the joint ventures. A higher ownership by the parents in joint ventures indicates that they have a higher percentage of board members. Third, the relative importance of a set of bargaining power is identified with hypothesis testing of the relationship between control and bargaining power. There is little evidence that the relationship between bargaining power and control is not closely associated. Fourth, the relative importance of resource contribution by parents is identified and hypotheses are tested on the relationship between control and resource contribution factors. The results are strongly supported that the relationships between resource contributions in terms of physical, invisible, financial, human, and organizational ability of parents and their control has significant and positive associations. Fifth, the relative importance of a set of motives for international joint venture formation is identified and hypotheses are tested on the relationship between control and motivation factors in terms of technological acquisition, knowledge learning, risk sharing, competitive strategy consideration, resource complementarily, market expansion. The findings reveal a limited number of significant correlations between motivation factors and control

A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials

Road transport accounted for 20% of global total greenhouse gas emissions in 2020, of which 30% come from road freight transport (RFT). Modeling the modern challenges in RFT requires the integration of different freight modeling improvements in, e.g., traffic, demand, and energy modeling. Recent developments in \u27Big Data\u27 (i.e., vast quantities of structured and unstructured data) can provide useful information such as individual behaviors and activities in addition to aggregated patterns using conventional datasets. This paper summarizes the state of the art in analyzing Big Data sources concerning RFT by identifying key challenges and the current knowledge gaps. Various challenges, including organizational, privacy, technical expertise, and legal challenges, hinder the access and utilization of Big Data for RFT applications. We note that the environment for sharing data is still in its infancy. Improving access and use of Big Data will require political support to ensure all involved parties that their data will be safe and contribute positively toward a common goal, such as a more sustainable economy. We identify promising areas for future opportunities and research, including data collection and preparation, data analytics and utilization, and applications to support decision-making

Benchmarking and identification of best practice associated with industrial water use in UK

In the wake of the phenomenal growth rate of fresh water use globally, the need to ensure security of supply and maintain optimal competiveness in water business has heralded the increasing awareness to measure and compare water use by means of meaningful metrics, performance indicators and benchmarks. Thus, in view of the historically intensive use of water by UK industry, this research set out to benchmark the sector’s water use; the overarching aim being to deduce performance gaps in water use by industry, identify best-in-class practices associated with industrial water use, and proffer efficient improvement strategies for optimal performance in the sector. To achieve this aim, and in line with the research funder’s anticipated outcome of this study, a benchmarking software called “i-Water Benchmarking Tool” was developed. Although, few tools and methodologies are available for benchmarking performance with respect to water usage, but most of these tools are mainly domestic water use specific, developed by, and are within the ownership of commercial organizations. Hence, the rationale behind the software development is to provide a robust, user-friendly and accessible tool that can be used to benchmark water use across industrial subsectors and establish the basis for improvement in performance. Based on the foregoing, comprehensive data were sourced from UK water undertakings, trade bodies and environmental agencies, and used to conduct statistical data analyses and performance benchmarking. Results of the analyses revealed that in England and Wales, from 2003 – 2013, “Metals” constituted the highest consumptive water user (43% water use in the manufacturing sector alone), even with the sub-sector’s 51.31% decline in water use during this period; followed by “Chemicals” (20.52%) with a 45.86% decrease in water use. The third, “Petrochemicals” (15.15%), with a 54.02% water use reduction; fourth, “Paper and printing” (6.15%), showing a 51.64% decline; then, “Food and Drinks” being the fifth most intensive water user (5.32%) also indicated a 17.73% decrease in water use. For Scotland, from 2008/09 to 2014/15, “Distilled potable alcoholic beverages” took up the largest consumptive water (30.21%), but exhibited a 16.51% water use decline; the second, “Basic pharmaceutical products” (26.61%) had an 18.51% water use decrease; the third, “Paper and paperboard” (19.35%), revealing a 31.90% increase in water use; fourth, “Beer” (4.91%) with an 18.42% water use decline; then the fifth, “Liquid milk and cream” (4.26%) with a 0.42% reduction in water use between 2008/09 and 2014/15 also. Lastly, in Northern Ireland, from 2011-12 to 2013-14, “Food” used the largest water (57.39%) showing a 3.823% decline in water use during this period; “Non Metals” (10%) with 5.32% decrease; “Electronics” (8.77%) with 20.42% reduction; “Chemical” (8.76%) with a 10.12% water use increase; and lastly, “Drink” (6.33%) with an 11.68% decline in water use. To this end, with 80% of the products indicating a decline in water use, it is inferred that industrial water use in the UK is significantly declining. Accordingly, of the 53 benchmarked companies, 3 companies’ water use performance were ranked “Excellent”; 20 companies, “Average”; while the remaining 30 companies’ performance were “Poor”. In sum, it is envisaged that this project will lead to the definition of a methodology that can be applied to produce same outputs for sectors not covered in this initial project

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Strategies to Minimize the Bullwhip Effect in the Electronic Component Supply Chain

Supply chain leaders in the information technology industry face challenges regarding their ability to mitigate amplified demand and supply variability in a supply chain network--the bullwhip effect--and reduce adverse implications on their component supply chain networks. The purpose of this multiple case study was to explore the strategies supply chain leaders in the United States used to reduce the bullwhip effect. Bullwhip effect theory served as the conceptual framework. Participants in the study were 5 purposefully selected supply chain leaders in the state of Texas who successfully implemented strategies to reduce the bullwhip effect on their networks. Data were collected from semistructured interviews and analysis of documents from the participants\u27 websites. The data were analyzed using the 5 data analysis steps consistent with Yin\u27s approach: collection, stratification, reassembly, interpretation, and conclusion. Four themes emerged from data analysis: (a) collaboration strategy, (b) communication strategy, (c) component shortage reduction strategy, and (d) resource management strategy. Supply chain leaders might use the findings of this study to reduce the bullwhip effect within their networks and improve their profitability. The implications for positive social change include the potential for leaders to improve environmental sustainability by using effective supply chain strategies to reduce the accumulation of excess inventories, reduce transportation fuel usage, and lessen the consumption of natural resources

Impact of the merger between British Petroleum Southern Africa (BPSA) and Castrol South Africa on Blendcor (A joint venture between Shell Southern Africa (SSA) and British Petroleum South Africa).

Thesis (MBA) - University of Natal, 2003.Blendcor (Pty) Limited is a joint venture lubricants blending and grease manufacturing plant and equally owned by its shareholders, British Petroleum Southern Africa and Shell South Africa. BP purchased Castrol worldwide in March 2000. The merger of BP and Castrol has created opportunities for consolidation of production at Blendcor. The inclusion of the Castrol lubes portfolio would increase current production at Blendcor to approximately 150 million liters per annum. The purpose of this research is to establish if the merger between BP and Castrol would have a positive or negative effect on Blendcor. We begin this research by seeking an understanding of the strategy framework and its role in assisting a company to achieve its objectives. The framework starts by explaining how strategy is formulated, the development of a vision, mission statement, the examination of the company's external environment, the company's internal environment, the impact of globalisation, the company's long-term goals, and finally organizational structure and leadership. Emphasis is placed on companies that employ Joint Ventures, Mergers and Alliances as grand strategies. The history of the Oil industry in South Africa, the history of Blendcor's partners, a brief history and background of Blendcor, followed by a discussion on the merger of BP and Castrol, and its impact on Blendcor, is examined. Blendcor is then evaluated by conducting a SWOT analysis. It's strengths; weaknesses, opportunities and threats are discussed briefly. The current strategy employed by Blendcor is subsequently evaluated against the suitability criteria. The plant is benchmarked against other plants worldwide in terms of cost and production. The strategy development process at Blendcor is then evaluated to determine the synergies of the leadership team. The merger is then profiled using the PIMS model to determine whether the merger was a good or bad decision. Finally, various recommendations are made to improve the plant and its processes. The replacement of Blendcor's Information system is discussed in length and the lack of a suitable measurement system is highlighted