Search results

1 – 10 of over 1000
Click here to view access options
Article
Publication date: 14 May 2018

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…

Downloads
711

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.

Details

VINE Journal of Information and Knowledge Management Systems, vol. 48 no. 2
Type: Research Article
ISSN: 2059-5891

Keywords

Click here to view access options
Article
Publication date: 6 July 2018

Y.P. Tsang, K.L. Choy, C.H. Wu, G.T.S. Ho, Cathy H.Y. Lam and P.S. Koo

Since the handling of environmentally sensitive products requires close monitoring under prescribed conditions throughout the supply chain, it is essential to manage…

Downloads
3265

Abstract

Purpose

Since the handling of environmentally sensitive products requires close monitoring under prescribed conditions throughout the supply chain, it is essential to manage specific supply chain risks, i.e. maintaining good environmental conditions, and ensuring occupational safety in the cold environment. The purpose of this paper is to propose an Internet of Things (IoT)-based risk monitoring system (IoTRMS) for controlling product quality and occupational safety risks in cold chains. Real-time product monitoring and risk assessment in personal occupational safety can be then effectively established throughout the entire cold chain.

Design/methodology/approach

In the design of IoTRMS, there are three major components for risk monitoring in cold chains, namely: wireless sensor network; cloud database services; and fuzzy logic approach. The wireless sensor network is deployed to collect ambient environmental conditions automatically, and the collected information is then managed and applied to a product quality degradation model in the cloud database. The fuzzy logic approach is applied in evaluating the cold-associated occupational safety risk of the different cold chain parties considering specific personal health status. To examine the performance of the proposed system, a cold chain service provider is selected for conducting a comparative analysis before and after applying the IoTRMS.

Findings

The real-time environmental monitoring ensures that the products handled within the desired conditions, namely temperature, humidity and lighting intensity so that any violation of the handling requirements is visible among all cold chain parties. In addition, for cold warehouses and rooms in different cold chain facilities, the personal occupational safety risk assessment is established by considering the surrounding environment and the operators’ personal health status. The frequency of occupational safety risks occurring, including cold-related accidents and injuries, can be greatly reduced. In addition, worker satisfaction and operational efficiency are improved. Therefore, it provides a solid foundation for assessing and identifying product quality and occupational safety risks in cold chain activities.

Originality/value

The cold chain is developed for managing environmentally sensitive products in the right conditions. Most studies found that the risks in cold chain are related to the fluctuation of environmental conditions, resulting in poor product quality and negative influences on consumer health. In addition, there is a lack of occupational safety risk consideration for those who work in cold environments. Therefore, this paper proposes IoTRMS to contribute the area of risk monitoring by means of the IoT application and artificial intelligence techniques. The risk assessment and identification can be effectively established, resulting in secure product quality and appropriate occupational safety management.

Details

Industrial Management & Data Systems, vol. 118 no. 7
Type: Research Article
ISSN: 0263-5577

Keywords

Click here to view access options
Article
Publication date: 1 March 2006

Albert P.C. Chan, Y.H. Chiang, Stephen W.K. Mak, Lennon H.T. Choy and M.W.W James

Efficient manpower planning has been recognized as a critical aspect for the development of an economy. In 2001, the Works Bureau of the Hong Kong SAR Government…

Abstract

Efficient manpower planning has been recognized as a critical aspect for the development of an economy. In 2001, the Works Bureau of the Hong Kong SAR Government (predecessor of Environment, Transport and Works Bureau) commissioned an HKPolyU consultancy team to develop a computer‐based model to estimate the demand for different categories of construction personnel. This article presents the concept and features of the manpower demand‐forecasting model developed for the construction industry of Hong Kong. The forecasting model is formulated on the basis of the labour multiplier approach by deriving the relationship between the number of workers required and the project expenditure in the given project duration. Multipliers for 61 project types were derived for 38 labour trades using completed project data. The labour demand by occupation for each project can then be estimated by multiplying the corresponding multipliers and the estimated project expenditure. Several unique features of the model have been developed, including “normalization” and “contract cost adjustment factor”. Normalizing the labour multipliers can facilitate the prediction of occupational labour requirements at different stages of a construction project. The adjustment factor is introduced to eliminate the discrepancy between the original estimates and final contract values so as to enhance the estimation accuracy. The model can also be used to predict the number of jobs created for a given level of investment. The government can apply this model to check and compare which project types will generate most jobs before committing public money. This model could be easily adopted and adapted by foreign construction authorities while planning manpower.

Details

Construction Innovation, vol. 6 no. 1
Type: Research Article
ISSN: 1471-4175

Keywords

Click here to view access options
Article
Publication date: 1 May 2003

K.L. Choy and W.B. Lee

A corporation’s global supply chain usually consists of enterprises and manufacturers that are graphically dispersed around the world, whereby each company is involved in…

Downloads
5539

Abstract

A corporation’s global supply chain usually consists of enterprises and manufacturers that are graphically dispersed around the world, whereby each company is involved in a wide variety of supply chain activities such as order fulfilment, international procurement, acquisition of information technology, manufacturing, and customer service. Therefore, continuously tracking performance of suppliers and an appropriate selection mechanism is one of the crucial activities in supply chain management. This paper presents an intelligent generic supplier management tool (GSMT) using the case‐based reasoning (CBR) technique for outsourcing to suppliers and automating the decision making process when selecting them. The development of GSMT and how the CBR technique is applied is then given, followed by an application of GSMT in Honeywell Consumer Products (Hong Kong) Limited.

Details

Supply Chain Management: An International Journal, vol. 8 no. 2
Type: Research Article
ISSN: 1359-8546

Keywords

Click here to view access options
Article
Publication date: 11 September 2019

Valerie Tang, K.L. Choy, G.T.S. Ho, H.Y. Lam and Y.P. Tsang

The purpose of this paper is to develop an Internet of medical things (IoMT)-based geriatric care management system (I-GCMS), integrating IoMT and case-based reasoning…

Abstract

Purpose

The purpose of this paper is to develop an Internet of medical things (IoMT)-based geriatric care management system (I-GCMS), integrating IoMT and case-based reasoning (CBR) in order to deal with the global concerns of the increasing demand for elderly care service in nursing homes.

Design/methodology/approach

The I-GCMS is developed under the IoMT environment to collect real-time biometric data for total health monitoring. When the health of an elderly deteriorates, the CBR is used to revise and generate the customized care plan, and hence support and improve the geriatric care management (GCM) service in nursing homes.

Findings

A case study is conducted in a nursing home in Taiwan to evaluate the performance of the I-GCMS. Under the IoMT environment, the time saving in executing total health monitoring helps improve the daily operation effectiveness and efficiency. In addition, the proposed system helps leverage a proactive approach in modifying the content of a care plan in response to the change of health status of elderly.

Originality/value

Considering the needs for demanding and accurate healthcare services, this is the first time that IoMT and CBR technologies have been integrated in the field of GCM. This paper illustrates how to seamlessly connect various sensors to capture real-time biometric data to the I-GCMS platform for responsively supporting decision making in the care plan modification processes. With the aid of I-GCMS, the efficiency in executing the daily routine processes and the quality of healthcare services can be improved.

Details

Industrial Management & Data Systems, vol. 119 no. 8
Type: Research Article
ISSN: 0263-5577

Keywords

Click here to view access options
Article
Publication date: 1 October 2002

K.L. Choy and W.B. Lee

Many companies that were once centrally involved in the actual manufacture of products, and the delivery of their supporting services, now find themselves primarily…

Downloads
3444

Abstract

Many companies that were once centrally involved in the actual manufacture of products, and the delivery of their supporting services, now find themselves primarily engaged in integrating a number of other organizations, some of which they may own but many of which will be independent, each of which goes to make up a particular supply network. Consequently, continuously tracking performance of suppliers and an appropriate selection mechanism is one of the crucial activities in managing this supply network. This paper presents an intelligent generic supplier management tool (GSMT) using the case‐based reasoning (CBR) technique for outsourcing to suppliers and automating the decision‐making process when selecting them. The development of GSMT and how the CBR technique is applied is then given, followed by an application of GSMT in Honeywell Consumer Products (Hong Kong) Limited.

Details

Logistics Information Management, vol. 15 no. 4
Type: Research Article
ISSN: 0957-6053

Keywords

Click here to view access options
Book part
Publication date: 20 August 2018

Bartosz Sawik

In this chapter, four bi-objective vehicle routing problems are considered. Weighted-sum approach optimization models are formulated with the use of mixed-integer…

Abstract

In this chapter, four bi-objective vehicle routing problems are considered. Weighted-sum approach optimization models are formulated with the use of mixed-integer programming. In presented optimization models, maximization of capacity of truck versus minimization of utilization of fuel, carbon emission, and production of noise are taken into account. The problems deal with real data for green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country, and La Rioja, Spain.

Heterogeneous fleet of trucks is considered. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Modern logistic companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, and utilization of fuel, carbon emission, and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution. The computational experiments were performed using the AMPL programming language and the CPLEX solver.

Click here to view access options
Article
Publication date: 1 March 2016

Christodoulos Nikou and Socrates J. Moschuris

Supplier selection for defence procurement is a crucial function of a Ministry of Defence. The Ministry spends huge amounts of money each year to procure a vast array of…

Abstract

Supplier selection for defence procurement is a crucial function of a Ministry of Defence. The Ministry spends huge amounts of money each year to procure a vast array of equipment, goods and services. The ongoing financial crisis demands less subjective and more cost-saving methods for selecting a supplier. The approach advocated in this article integrates Analytic Hierarchy Process (AHP) with Goal Programming (GP) in order to combine conflicting criteria to select the best suppliers and allocate optimum order quantities among them. This paper presents a model close to real-world situations. Findings demonstrate that cost savings is a feasible result along with a viable combination of conflicting criteria in the suppliers' selection area.

Details

Journal of Public Procurement, vol. 16 no. 1
Type: Research Article
ISSN: 1535-0118

Click here to view access options
Article
Publication date: 1 June 2004

K.L. Choy, W.B. Lee and Victor Lo

In this paper, a server‐based enterprise collaborative management system using enterprise application integration technology is developed for trial implementation at…

Downloads
6817

Abstract

In this paper, a server‐based enterprise collaborative management system using enterprise application integration technology is developed for trial implementation at Honeywell Consumer Products (Hong Kong) Limited, in the area of supplier relationship management. The system facilitates supplier selection using an integrative case‐based supplier selection and help desk approach to select the most appropriate suppliers, based on their past performance records from a case‐based warehouse. Discusses a case study to integrate Honeywell's supplier rating system and product coding system by case‐based reasoning technique to select preferred suppliers during the new product development process. Finds that the outsource cycle time from the searching of potential suppliers to the allocation of orders is greatly reduced while performance of suppliers can be monitored simultaneously.

Details

Journal of Enterprise Information Management, vol. 17 no. 3
Type: Research Article
ISSN: 1741-0398

Keywords

Click here to view access options
Article
Publication date: 25 October 2011

S.I. Lao, K.L. Choy, G.T.S. Ho, Y.C. Tsim and C.K.H. Lee

With the increasing concerns about food management, attention is placed on the monitoring of different potential risk factors for food handling. Therefore, the purpose of…

Downloads
2087

Abstract

Purpose

With the increasing concerns about food management, attention is placed on the monitoring of different potential risk factors for food handling. Therefore, the purpose of this paper is to propose a system that helps facilitate and improve the quality of decision making, reduces the level of substandard goods, and facilitates data capturing and manipulation, to help a warehouses improve quality assurance in the inventory‐receiving process with the support of technology.

Design/methodology/approach

This system consists of three modules, which integrate the radio frequency identification (RFID) technology, case‐based reasoning (CBR), and fuzzy reasoning (FR) technique to help monitor food quality assurance activities. In the first module, the data collection module, raw warehouse and work station information are collected. In the second module, the data sorting module, the collected data are stored in a database. In this module, data are decoded, and the coding stored in the RFID tags are transformed into meaningful information. The last module is the decision‐making module, through which the operation guidelines and optimal storage conditions are determined.

Findings

To validate the feasibility of the proposed system, a case study was conducted in food manufacturing companies. A pilot run of the system revealed that the performance of the receiving operation assignment and food quality assurance activities improved significantly.

Originality/value

In summary, the major contribution of this paper is to develop an effective infrastructure for managing food‐receiving process and facilitating decision making in quality assurance. Integrating CBR and FR techniques to improve the quality of decision making on food inventories is an emerging idea. The system development roadmap demonstrates the way to future research opportunities for managing food inventories in the receiving operations and implementing artificial intelligent techniques in the logistics industry.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 8
Type: Research Article
ISSN: 1741-038X

Keywords

1 – 10 of over 1000