Search results

The purpose of this paper is to investigate the impact of radio frequency identification (RFID) deployment at an airport baggage‐handling system (BHS).

The impact of number of RFID readers at different power levels with varying conveyor (i.e. baggage‐handling conveyors) speeds on timely delivery of baggage is studied via simulation. The layout of the BHS at the Hong Kong International Airport and data pertinent to its RFID deployment in 2005 are used to build the simulation model. The RFID read logic is based on the equations defined as a function of the number of tags and the time the tags spend in the interrogation zone for each reader in order to capture possible read‐rate issues realistically.

The identification capability of the BHS studied in this paper is a result of its combined ability to identify tags via RFID technology on straight and circulating conveyors, as well as at the manual recovery station for unidentified bags on circulating conveyors. Overall, timely delivery of bags to gates, as a performance metric, increases as the identification capability is improved. The controllable factors that affect the identification capability are the conveyor speed, which determines the time a tag stays in the interrogation zone; the reader antenna power level, which determines the size of the interrogation zone; and the number of reader antennas in the system that increases the likelihood of not missing tags. This paper shows that “the higher the number of reader antennas and the higher the power level on them, the better” approach is not correct.

Unlike typical simulation studies related to RFID deployment where read‐rate issues are considered to be non‐existent, this paper captures read rate in a realistic manner in the simulation model by incorporating the effect of number of RFID tags in the interrogation zone and time that RFID tags spend in the interrogation zone due to baggage conveyor speed. Such a simulation approach can be used as a system design tool in order to investigate the impact of RFID‐specific parameters on system‐level performance.

The purpose of this paper is to present the development of an architecture for real‐time routing of automated guided vehicles (AGV) in a random flexible manufacturing system (FMS).

AGV routing problem is modeled using an evolutionary algorithm‐based intelligent path planning model, which handles vehicle assignments to material handling requests and makes routing decisions with the objective of maximizing the system throughput. The architecture is implemented on a 3‐layer software environment in order to evaluate the effectiveness of the proposed model.

The proposed architecture, along with the evolutionary algorithm‐based routing model, is implemented in a simulated FMS environment using hypothetical production data. In order to benchmark the performance of the path planning algorithm, the same FMS model is run by traditional dispatching rules. The analysis shows that the proposed routing model outperforms the traditional dispatching rules for real‐time routing of AGVs in many cases.

Future work includes expanding the scope of the current work by developing and implementing other routing models and benchmarking them against the proposed model on different performance measures.

The implementation of evolutionary algorithms in real‐time routing of AGVs is unique. In addition, due to its modularity, the proposed 3‐layer architecture can allow effective and efficient integration of different real‐time routing algorithms; therefore it can be used as a benchmarking platform.

This paper investigates interference mitigation and read rate improvement by using novel power control and graph‐based scheduling schemes for radio frequency identification (RFID) systems.

The first method is a distributed power control (DPC) scheme proposed as an alternative to listen‐before‐talk (LBT) for RFID systems specified under CEPT regulations. The DPC algorithm employs reader transmission power as the system control variable to achieve a desired read range and read rate without causing unwanted interference. The second approach is graph‐based scheduling, which uses a graph coloring‐based approach to temporally separate readers with overlapping interrogation zones. The scheduling of the timeslots is carried out so as to offer better efficiency for each reader.

This paper shows that power control, graph theory, collision probability analysis along with timeslot scheduling schemes can be widely adapted to solve general RFID problems. The study shows that selection of timeslot allocation schemes should be carried out after carefully analysing the process/workflow in the application domain. While fair scheduling schemes can be applicable to stable manufacturing environments, event‐triggered scheduling schemes are more effective in fairly chaotic environments.

The study shows that the proposed interference mitigation and read rate improvement techniques can be generalized to assist in design, development, and implementation of a variety of RFID‐based systems, ranging from supply chain level operations to shop floor control. The proposed techniques improve not only the reliability of RFID systems but, more importantly, improve business processes that rely on RFID data.

This paper presents an overview on the Auto‐ID (Automatic Identification) technologies testbed that has been established at the University of Missouri‐Rolla (UMR) with the objective of supporting research, development, and implementation of Auto‐ID technologies in network‐centric manufacturing environments.

UMR's Auto‐ID testbed uses a unique hardware‐in‐the‐loop simulation methodology, which integrates decision‐making model development with the design of networking topology and data routing/scheduling schemes, in order to develop, test, and implement viable Auto‐ID solutions. The methodology is founded on a 3‐level integrated model: controller simulation, distributed controller simulation, and distributed controller simulation with hardware‐in‐the‐loop.

This paper discusses two case studies that highlight the effective use of RFID technology, its potential advantages, challenges, and deficiencies stemming from particular applications. These applications include dock doors, automated guided vehicles, conveyor and automated storage/retrieval systems, integration of RFID middleware with programmable logic controllers, and inventory management of time‐sensitive materials.

The paper presents an innovative idea: hardware‐in‐the‐loop simulation methodology to design automation systems. The approach has been implemented on a variety of applications, which are presented in the paper as case studies.

The purpose of this study is to verify all factors that promote renewable energy (RE) consumption. Past studies have shown that financial development (FD) and economic growth (EG) are the major drivers toward RE development, while oil prices had mixed outcomes in different regions by different studies.

Global warming effects have been the major reason of the transition by nations from fossil fuel use to RE sources that are considered as friendly to the environment. This research uses the fixed effects and random effects techniques, to ascertain the factors which impact RE development. The generalized linear model is also used to check the robustness of the Fixed Effects and Random Effects models’ results, while the Kao, Pedroni and Westerlund tests are used to check cointegration in the specified model.

The major findings of this study show the importance of EG and FD in promoting RE development. Oil prices, inflation rate and public sector credit present a negative effect on RE development, while foreign direct investment does not significantly impact RE development.

This research recommends the use of FD in promoting RE sources, as well as the stabilization of oil prices and consumer prices.

This research is important because it specifies the three proxies of FD, together with foreign direct investment inflation rate, EG and oil prices, in modeling RE. By investigating the impact of oil prices on RE in the emerging seven economies, this research becomes one of the few studies done in this region, as per the authors’ knowhow.

Flexible automation robotic systems and off‐line programming methods have recently received much attention. Studies the problem of robot auto‐marking and auto‐cutting of shipbuilding panels, using an integrated computer aided design/manufacturing (CAD/CAM) system based on computer technology and off‐line programming of the robot. The following three points are focused on in this paper: marking and cutting information of the panel’s CAD model; measurement of the panel’s deformation and its compensation algorithm; robot auto‐making and auto‐cutting of the panel using the CAM system. Robot auto‐marking and auto‐cutting of shipbuilding panels solves the difficulty associated with panel marking and cutting by hand. Furthermore this system possesses high processing precision and automatically compensates for the deformation of the panel. Our experiments prove the feasibility and efficiency of this system at the end of this paper.

The purpose of this paper is to introduce a more practical approach for supply chain performance measurement (SCPM) and to approve the promising role of internet of things (IoT) technologies in SCPM systems.

This is a conceptual paper that includes literature review analysis, designing a new approach for SCPM, and a case study scenario for proving its applicability.

The case study scenario shows that IoT can enhance SCPM, as it has the capability to enable real-time data collection, increase data efficiency as long as enable real-time communication within the supply chain (SC).

The proposed approach can help to develop performance measurement systems and applications enabled by IoT technologies. These systems can be used to monitor, manage, and control the overall SC in real time and in a more integrated and cooperative manner.

This paper provides a structured systems building approach tailored to show how to employ IoT technologies in the field of SCPM. This approach could help in establishing new performance measurement applications, and it is believed that both practitioners and researchers will benefit from it.

This paper aims to examine the effect of inventory information sharing on inventory efficiency and its intervening effect of information technology (IT) capability in manufacturing firms.

Stratified random sampling and filter questions selected targeted respondents, and an online survey collected 124 completed questionnaires from Malaysian manufacturing firms. partial least squares structural equation modeling (PLS-SEM) examined the structural model and hypothesis statement. An analysis of importance-performance map analysis (IPMA) test identified the relative importance drivers of inventory efficiency.

The findings showed that enhanced IT capabilities in manufacturing firms mediate a positive relationship between inventory sharing and inventory efficiency.

This study portrays the relationship between inventory level, demand and information sharing. The research was carried out only within Malaysian manufacturing firms.

These findings will enable the management of manufacturing firms to design and visualise their inventory levels and share best practices across supply chain networks to achieve effective and optimised inventory planning.

This study illustrates an intervention model that offers a direct and indirect impact of IT capabilities that allow scholars to close inventories productivity gaps in research.

This paper extends the limited literature on the sharing of inventory information and inventory productivity, notably from a strategic management perspective. The findings help scholars clearly understand the information systems capability and its mediating impact on information sharing and inventory efficiency’s relationship in the manufacturing sector. Moreover, demand information sharing affected the dynamic supply chain.

This paper aims to examine the relationship between supply chain quality management practices and their impact on supply chain performance. The authors define and operationalize supply chain quality management practices that enhance knowledge creation and learning in a supply chain.

Data are collected from logistics and supply chain managers in the USA to examine the validity and reliability of the model for supply chain quality.

The empirical result provides support for the reliability and validity of the proposed model, the constructs used in the model, and the interrelationships among key constructs of supply chain quality. The authors show that trust is the main predictor of supply chain quality practices and supply chain quality performance outcomes. In addition, the findings show that the impact of trust on process improvement is mediated by information sharing, inter-firm trust and information sharing are significant predictors of supply chain satisfaction, and inter-firm trust and process improvement are significant predictors of supply chain performance. Implications of the research for the theory and practice of supply chain management and quality management are presented.

This study provides important insights into effective implementation of quality management across the supply chain. Supply chain managers should realize that achieving improvement in many supply chain activities such as information sharing or process improvement requires organizations to be engaged in trust-based activities. In that regard, it is important for supply chain managers to be engaged in developing relationships with their supply chain partners that enhance inter-organizational trust.

This is the first study that examines a supply chain quality management model from the learning perspective. The authors validate the supply chain quality framework proposed by Parast (2103) through operationalization of the constructs, development of the relationship among key supply chain quality practices and empirical assessment of the structural model for supply chain quality.

The purpose of this paper is to investigate the superior relationship between blood lipid- and cardiovascular disease (CVD)-related hematological parameters using superior grey relational analysis (GRA).

A total of 294 individuals who underwent simultaneous routine blood examination and blood lipid examination in the Physical Examination Center of the First Affiliated Hospital of Shantou University Medical College were included in this study. Superior GRA was performed to find out the superior factor in CVD-related hematological parameters and blood lipids. CVD-related hematological parameters included red blood cell distribution width, white cell count, and platelet count, platelet distribution width, mean platelet volume, as well as platelet crit. The indicators of blood lipids analyzed here consist of low-density lipoprotein, high-density lipoprotein, triglyceride and total cholesterol.

The results showed that all the grey relational degree of hematological parameters and blood lipids were over 0.8; the superior factor in hematological parameters was PLT, whereas TC was the superior factor in blood lipids.

Findings of this study suggested that hematological parameters are closely related to blood lipids and a potential role for hematological parameters in the prediction of dyslipidemia, which need further study; TC has the greatest influence on hematological parameters, whereas TG displays a minimal impact.

To the authors’ best knowledge, it was the first study to analyze the relationship between various CVD-related hematological parameters and blood lipids via superior GRA.