Y.P. Tsang, K.L. Choy, P.S. Koo, G.T.S. Ho, C.H. Wu, H.Y. Lam and Valerie Tang
This paper aims to improve operational efficiency and minimize accident frequency in cold storage facilities through adopting an effective occupational safety and health program…
Abstract
Purpose
This paper aims to improve operational efficiency and minimize accident frequency in cold storage facilities through adopting an effective occupational safety and health program. The hidden knowledge can be extracted from the warehousing operations to create the comfortable and safe workplace environment.
Design/methodology/approach
A fuzzy association rule-based knowledge management system is developed by integrating fuzzy association rule mining (FARM) and rule-based expert system (RES). FARM is used to extract hidden knowledge from real operations to establish the relationship between safety measurement, personal constitution and key performance index measurement. The extracted knowledge is then stored and adopted in the RES to establish an effective occupational and safety program. Afterwards, a case study is conducted to validate the performance of the proposed system.
Findings
The results indicate that the aforementioned relationship can be built in the form of IF-THEN rules. An appropriate safety and health program can be developed and applied to all workers, so that they can follow instructions to prevent cold induced injuries and also improve the productivity.
Practical implications
Because of the increasing public consciousness of occupational safety and health, it is important for the workers in cold storage facilities where the ambient temperature is at/below 10°C. The proposed system can address the social problem and promote the importance of occupational safety and health in the society.
Originality/value
This study contributes to the knowledge management system for improving the occupational safety and operational efficiency in the cold storage facilities.
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G.T.S. Ho, H.C.W. Lau, S.H. Chung, R.Y.K. Fung, T.M. Chan and C.K.M. Lee
This paper aims to develop a genetic algorithm (GA)‐based process knowledge integration system (GA‐PKIS) for generalizing a set of nearly optimal fuzzy rules in quality…
Abstract
Purpose
This paper aims to develop a genetic algorithm (GA)‐based process knowledge integration system (GA‐PKIS) for generalizing a set of nearly optimal fuzzy rules in quality enhancement based on the extracted fuzzy association rules in a supply chain network.
Design/methodology/approach
The proposed methodology provides all levels of employees with the ability to formulate nearly optimal sets of fuzzy rules to identify possible solutions for eliminating the number of defect items.
Findings
The application of the proposed methodology in the slider manufacturer has been studied. After performing the spatial analysis, the results obtained indicate that it is capable of ensuring the finished products with promising quality.
Research limitations/implications
In order to demonstrate the feasibility of the proposed approach, only some processes within the supply chain are chosen. Future studies can advance this research by applying the proposed approach in different industries and processes.
Originality/value
Because of the complexity of the logistics operations along the supply chain, the traditional quality improvement approaches cannot address all the quality problems automatically and effectively. This newly developed GA‐based approach can help to optimize the process parameters along the supply chain network.
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Henry Lau, C.K.M. Lee, Dilupa Nakandala and Paul Shum
The purpose of this paper is to propose an outcome-based process optimization model which can be deployed in companies to enhance their business operations, strengthening their…
Abstract
Purpose
The purpose of this paper is to propose an outcome-based process optimization model which can be deployed in companies to enhance their business operations, strengthening their competitiveness in the current industrial environment. To validate the approach, a case example has been included to assess the practicality and validity of this approach to be applied in actual environment.
Design/methodology/approach
This model embraces two approaches including: fuzzy logic for mimicking the human thinking and decision making mechanism; and data mining association rules approach for optimizing the analyzed knowledge for future decision-making as well as providing a mechanism to apply the obtained knowledge to support the improvement of different types of processes.
Findings
The new methodology of the proposed algorithm has been evaluated in a case study and the algorithm shows its potential to determine the primary factors that have a great effect upon the final result of the entire operation comprising a number of processes. In this case example, relevant process parameters have been identified as the important factors causing significant impact on the result of final outcome.
Research limitations/implications
The proposed methodology requires the dependence on human knowledge and personal experience to determine the various fuzzy regions of the processes. This can be fairly subjective and even biased. As such, it is advisable that the development of artificial intelligence techniques to support automatic machine learning to derive the fuzzy sets should be promoted to provide more reliable results.
Originality/value
Recent study on the relevant topics indicates that an intelligent process optimization approach, which is able to interact seamlessly with the knowledge-based system and extract useful information for process improvement, is still seen as an area that requires more study and investigation. In this research, the process optimization system with an effective process mining algorithm embedded for supporting knowledge discovery is proposed for use to achieve better quality control.
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Y.N. Au Yeung, L. Gow, C.C. Lai, W.F. Ho, A. Sivan and J. Ledesma
Action research involves practitioners in attempting to improvetheir own teaching through cycles of planning, acting, observing andreflecting. This idea was adopted by a group of…
Abstract
Action research involves practitioners in attempting to improve their own teaching through cycles of planning, acting, observing and reflecting. This idea was adopted by a group of interested staff to evaluate the industrial training in the third year of the four‐year sandwich course, B.Eng. (Hons) in Building Services Engineering, at Hong Kong Polytechnic. As there are foreseen difficulties in locating suitable and adequate high quality industrial placements, research was carried out to evaluate the effectiveness of the existing arrangement. Assesses attitudes of BSE staff, students and industrial supervisors towards the training. Results of the survey indicated that objectives of the training were not wholly fulfilled. Suggestions are included to improve the management of the training system.
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Carmen Kar Hang Lee, Y.K. Tse, G.T.S. Ho and K.L. Choy
The emergence of the fast fashion trend has exerted a great pressure on fashion designers who are urged to consider customers’ preferences in their designs and develop new…
Abstract
Purpose
The emergence of the fast fashion trend has exerted a great pressure on fashion designers who are urged to consider customers’ preferences in their designs and develop new products in an efficient manner. The purpose of this paper is to develop a fuzzy association rule mining (FARM) approach for improving the efficiency and effectiveness of new product development (NPD) in fast fashion.
Design/methodology/approach
The FARM identifies the hidden relationships between product styles and customer preferences. The knowledge discovered help the fashion industry design new products which are not only fashionable, but are also saleable in the market.
Findings
To evaluate the proposed approach, a case study is conducted in a Hong Kong-based fashion company in which a real-set of data are tested to generate fuzzy association rules. The results reveal that the FARM approach can provide knowledge support to the fashion industry during NPD, shorten the NPD cycle time, and increase customer satisfaction.
Originality/value
Compared with traditional association rule mining, the proposed FARM approach takes the fuzziness of data into consideration and the knowledge represented in the fuzzy rules is in a more human-understandable structure. It captures the voice of the customer into fashion product development and provides a specific solution to deal with the challenges brought by fast fashion. In addition, it helps increase the innovation and technological capability of the fashion industry.
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Lawrence W.C. Lai and Frank T. Lorne
The types of innovation considered to be Schumpeterian can be very broad. What is an innovation? According to The Advanced Learner's Dictionary (Hornby, Gatenby, & Wakefield…
Abstract
The types of innovation considered to be Schumpeterian can be very broad. What is an innovation? According to The Advanced Learner's Dictionary (Hornby, Gatenby, & Wakefield, 1973, p. 545), an innovation is “something new that is introduced.” This covers both inventions and their introduction. Thus, introducing methods to a new market can certainly be a form of Schumpeterian innovation. Schumpeter, however, distinguished innovations (innovators) from inventions (inventors) (Swedberg, 1991, p. 173). He considered innovations as the prime movers in the capitalist process. Johannessen, Olsen, and Lumpkin (2001) dwell on six measures of the “newness” of an innovation based on his interpretation of Schumpeter and others, but glossed over the distinction between innovations and inventions. What, then, was Schumpeter's original formulation?
Vitus Mwinteribo Tabie, Chong Li, Wang Saifu, Jianwei Li and Xiaojing Xu
This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.
Abstract
Purpose
This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.
Design/methodology/approach
Following a brief introduction of titanium (Ti) alloys, this paper considers the near-α group of Ti alloys, which are the most popular high-temperature Ti alloys developed for a high-temperature application, particularly in compressor disc and blades in aero-engines. The paper is relied on literature within the past decade to discuss phase stability and microstructural effect of alloying elements, plastic deformation and reinforcements used in the development of these alloys.
Findings
The near-a Ti alloys show high potential for high-temperature applications, and many researchers have explored the incorporation of TiC, TiB SiC, Y2O3, La2O3 and Al2O3 reinforcements for improved mechanical properties. Rolling, extrusion, forging and some severe plastic deformation (SPD) techniques, as well as heat treatment methods, have also been explored extensively. There is, however, a paucity of information on SiC, Y2O3 and carbon nanotube reinforcements and their combinations for improved mechanical properties. Information on some SPD techniques such as cyclic extrusion compression, multiaxial compression/forging and repeated corrugation and straightening for this class of alloys is also limited.
Originality/value
This paper provides a topical, technical insight into developments in near-a Ti alloys using literature from within the past decade. It also outlines the future developments of this class of Ti alloys.
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Ning Qian, Muhammad Jamil, Wenfeng Ding, Yucan Fu and Jiuhua Xu
This paper is supposed to provide a critical review of current research progress on thermal management in grinding of superalloys, and future directions and challenges. By…
Abstract
Purpose
This paper is supposed to provide a critical review of current research progress on thermal management in grinding of superalloys, and future directions and challenges. By understanding the current progress and identifying the developing directions, thermal management can be achieved in the grinding of superalloys to significantly improve the grinding quality and efficiency.
Design/methodology/approach
The relevant literature is collected from Web of Science, Scopus, CNKI, Google scholar, etc. A total of 185 literature is analyzed, and the findings in the literature are systematically summarized. In this case, the current development and future trends of thermal management in grinding of superalloys can be concluded.
Findings
The recent developments in grinding superalloys, demands, challenges and solutions are analyzed. The theoretical basis of thermal management in grinding, the grinding heat partition analysis, is also summarized. The novel methods and technologies for thermal management are developed and reviewed, i.e. new grinding technologies and parameter optimization, super abrasive grinding wheel technologies, improved lubrication, highly efficient coolant delivery and enhanced heat transfer by passive thermal devices. Finally, the future trends and challenges are identified.
Originality/value
Superalloys have excellent physical and mechanical properties, e.g. high thermal stability, and good high-temperature strength. The superalloys have been broadly applied in the aerospace, energy and automobile industries. Grinding is one of the most important precision machining technologies for superalloy parts. Owing to the mechanical and physical properties of superalloys, during grinding processes, forces are large and a massive heat is generated. Consequently, the improvement of grinding quality and efficiency is limited. It is important to conduct thermal management in the grinding of superalloys to decrease grinding forces and heat generation. The grinding heat is also dissipated in time by enhanced heat transfer methods. Therefore, it is necessary and valuable to holistically review the current situation of thermal management in grinding of superalloys and also provide the development trends and challenges.
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Tempting as it is to be deterministic about world trade, Western economies are facing a number of new challenges. The collapse of hi‐tech stocks has prompted a re‐evaluation of…
Abstract
Tempting as it is to be deterministic about world trade, Western economies are facing a number of new challenges. The collapse of hi‐tech stocks has prompted a re‐evaluation of the new economy, yet traditional economic models no longer offer reliable predictions for the future. New information and communications technology has unquestionably jump‐started America’s economy, yet its re‐found prosperity is in many ways illusory. While the economists debate the relevance of classical theory, one inescapable fact confronts the nations of Europe: the inexorable decline of their population – and with it, their intellectual capital.
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Malte Thiede, Daniel Fuerstenau and Ana Paula Bezerra Barquet
The purpose of this paper is to review empirical studies on process mining in order to understand its use by organizations. The paper further aims to outline future research…
Abstract
Purpose
The purpose of this paper is to review empirical studies on process mining in order to understand its use by organizations. The paper further aims to outline future research opportunities.
Design/methodology/approach
The authors propose a classification model that combines core conceptual elements of process mining with prior models from technology classification from the enterprise resource planning and business intelligence field. The model incorporates an organizational usage, a system-orientation and service nature, adding a focus on physical services. The application is based on a systematic literature review of 144 research papers.
Findings
The results show that, thus far, the literature has been chiefly concerned with realization of single business process management systems in single organizations. The authors conclude that cross-system or cross-organizational process mining is underrepresented in the ISR, as is the analysis of physical services.
Practical implications
Process mining researchers have paid little attention to utilizing complex use cases and mining mixed physical-digital services. Practitioners should work closely with academics to overcome these knowledge gaps. Only then will process mining be on the cusp of becoming a technology that allows new insights into customer processes by supplying business operations with valuable and detailed information.
Originality/value
Despite the scientific interest in process mining, particularly scant attention has been given by researchers to investigating its use in relatively complex scenarios, e.g., cross-system and cross-organizational process mining. Furthermore, coverage on the use of process mining from a service perspective is limited, which fails to reflect the marketing and business context of most contemporary organizations, wherein the importance of such scenarios is widely acknowledged. The small number of studies encountered may be due to a lack of knowledge about the potential of such scenarios as well as successful examples, a situation the authors seek to remedy with this study.