Development of an OLAP Based Fuzzy Logic System for Supporting Put Away Decision

In today‘s rapidly changing and globally volatile world, manufacturers pay strong efforts on conducting lean production, outsourcing their components, and management on the complex supply chain. Warehouse management plays a vital role to be a successful player in the any kinds of industry which put-away process is a key activity that brings significant influence and challenges to warehouse performance. In this dynamic operating environment, minimizing the operation mistakes and providing accurate real time inventory information to stakeholder become the basic requirements to be an order qualifier. An OLAP based intelligent system called Fuzzy Storage Assignment System (FSAS) is proposed to increase availability of decision support data and convert the human knowledge into system for tackling the storage location assignment problem (SLAP). To validate the feasibility of this proposed system, a prototype will be worked out for a third party logistics company

A Real Time Quality Monitoring System for the Lighting Industry: A Practical and Rapid Approach Using Computer Vision and Image Processing (CVIP) Tools

In China, the manufacturing of lighting products is very labour intensive. The approach used to check quality and control production relies on operators who test using various types of fixtures. In order to increase the competitiveness of the manufacturer and the efficiency of production, the authors propose an integrated system. This system has two major elements: a computer vision system (CVS) and a real‐time monitoring system (RTMS). This model focuses not only on the rapid and practical application of modern technology to a traditional industry, but also represents a process innovation in the lighting industry. This paper describes the design and development of the prototyped lighting inspection system based on a practical and fast approach using computer vision and imaging processing (CVIP) tools. LabVIEW with IMAQ Vision Builder is the chosen tool for building the CVS. Experimental results show that this system produces a lower error rate than humans produce in the quality checking process. The whole integrated manufacturing strategy, aimed at achieving a better performance, is most suitable for a China and other labour intensive environments such as India.

Design and Development of an RFID-based HIS - A Case Study

The Healthcare industry involves critical activities where small mistakes could cause huge loss of life and incur massive financial losses. Improving operational efficiency and enhancing data correctness of patients are the prime targets of using hospital information system (HIS). Radio Frequency Identification (RFID) technology, with a unique ability to perform automatic data collection without any human intervention, has gained great interest in the healthcare industry. In this research, an RFID‐enabled HIS is proposed for improving operations in a hospital. This research presents the fundamentals of RFID, the benefits and its challenges, and also demonstrates three improved signature applications. It aims at providing the healthcare industry with a comprehensive understanding of RFID and its suitability for healthcare applications. The proposed system is considered to be suitably operational, practical, and affordable for healthcare organizations not only in China and Hong Kong, but also in other countries

A generic object-based support system for manufacturing processes

In this paper, an Object-Based Support System (OBSS), which is designed to be deployed in existing manufacturing firms with the objective to reorganise the job and process functions concerned, is proposed. The implementation of this system is based on the object technology concept, which considers most of the enterprise applications to be consisted of reusable software components, which are themselves built by other elements made up of relevant manufacturing data. Whenever there is any change of requirements, only the reusable software components are altered or just slightly modified to form a new component. More importantly, the flexibility and responsiveness of companies are greatly enhanced with the support of a generic object-based system that is specifically designed for improving the manufacturing activities of individual enterprises. The infrastructure with the developed and tested prototype system for validating its 'reconfigurability' is covered in the paper.Department of Industrial and Systems Engineerin

Infrastructure for implementing a responsive product development system: a case-based reasoning approach

Responding to unpredictable customer demands and changing design are common in the early stage of new product development, which requires good coordination and collaboration from almost all the functional disciplines of the company. Case-Based Reasoning (CBR), which combines the knowledge-based support philosophy with a simulation of human reasoning when past experience is used to create the design for customer requirement, is used as the underlying approach to establish the knowledge-base. This paper attempts to propose the infrastructure for building a responsive product development system, which is able to inspire designers to develop innovative designs. A Hybrid Information Management Module (HIMM) is responsible for case base transfer and relational database to enable efficient retrieval of the right information to the right person at right time. The significant contribution of this research concerns the introduction of a product development system, which enables the progressive inclusion of machine intelligence features and elements into the entire operation, thereby enhancing the implementation of a responsive product development environment.Department of Industrial and Systems Engineerin

Design and implementation of an object-oriented information management system

Competitive advantage is gained through operational excellence strategy while quality decisions, reviews and plans facilitate the production of quality products through the adoption of best practice as well as reduction of minimal waste and downtime. Efficient data collection with high accuracy is one of the key success factors to generate quality information, which has sufficient ability to transform data into economic value. However, inefficiency and ineffectiveness in the information life-cycle, including activities such as collect, store, use, analyse and share data, are often the common sick symptoms for most organisations. In general, the enterprises spend too much unnecessary resource on data collection and storage, and less on facilitating data analysis and sharing. This paper demonstrates how to analyse, design and develop an object-oriented information management system to re-engineer and improve the existing problems of inefficient data and information flow. In addition, it supports the data and information analysing technique to facilitate the decision-making and manufacturing process improvement. A case study on a manufacturing small and medium-sized enterprise has been conducted with promising results to validate the feasibility of the approach.Department of Industrial and Systems Engineerin

Real-time process mining system for supply chain network: OLAP-based fuzzy approach

Currently, companies active in the development of high-tech products have become more and more complex in the age of mass customisation. Not only do they have to focus on improving product quality, but rather on gaining experience to modify the current processes in order to streamline the integrated workflow. A Real-time Process Mining System (R-PMS) is developed to analyse the proposed XML-based process data for discovering the hidden relationships among processes. The new feature of this system is the incorporation of the process mining engine, which is characterised by the combined capabilities of the Online Analytical Processing (OLAP) and Fuzzy Logic (FL), to form a robust framework for highlighting the undesirable process setting and parameters for further improvement in a real-time manner. The simulation results indicated that the OLAP-based fuzzy approach was generally superior to those of conventional methods which offer higher flexibility on production process management with decision support ability. In this paper, the detailed architecture and a case study have been included to demonstrate the feasibility of the proposed system.Department of Industrial and Systems Engineerin

Using a fuzzy association rule mining approach to identify the financial data association

In the rapidly changing financial market, investors always have difficulty in deciding the right time to trade. In order to enhance investment profitability, investors desire a decision support system. The proposed artificial intelligence methodology provides investors with the ability to learn the association among different parameters. After the associations are extracted, investors can apply the rules in their decision support systems. In this work, the model is built with the ultimate goal of predicting the level of the Hang Seng Index in Hong Kong. The movement of Hang Seng Index, which is associated with other economics indices including the gross domestic product (GDP) index, the consumer price index (CPI), the interest rate, and the export value of goods from Hong Kong, is learnt by the proposed method. The case study shows that the proposed method is a feasible way to provide decision support for investors who may not be able to identify the hidden rules between the Hang Seng Index and other economics indices

Development of a process mining system for supporting knowledge discovery in a supply chain network

In today's competitive environment, business organizations are forced to maintain their competitive advantage by their ability to cut costs, increase revenue and uncover hidden issues. In order to enhance the visibility and transparency of value added information in a supply chain network, a process mining system is proposed for discovering a set of fuzzy association rules based on the daily captured logistics operation data, within the network. The proposed methodology provides all levels of employees with the ability to enhance their knowledge and understanding of the current business environment. Once interesting association rules have been extracted, organizations can identify the root-causes of quality problems in a supply chain and improve performance by fine-tuning the configuration of process parameters in specified processes. The application of the proposed methodology in a case company has also been studied. The prototype system has been developed and evaluated after performing a spatial analysis. The results obtained indicate that the system is capable of extracting high-quality and actionable information in the case company.Supply chain network Business intelligence Customer satisfaction