Search results

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.

This paper aims to address the association between the quality and quantity of information in supply chains and the costs and benefits of generating, using and sharing it.

The authors’ conceptual framework draws on multiple disciplines and theories of the value and use of product information. Controllable aspects of information, its quality and quantity, are the focus of the study as drivers of firm and chain performance. Structural equation models of constructs at two stages of the Australian red meat supply chain are employed, using data from a survey of 81 sheep and cattle breeders and commercial producers.

Information quality influences performance more for some product attributes than others and is more influential than is information quantity. Information sharing for many attributes generates benefits only at high cost. Investment in measurement and transmission technologies is supported for intrinsic and extrinsic measures of quality. Differences in respondents' evaluation of information quality are interpreted as evidence of persistent chain failure.

To the authors' knowledge, this is the first attempt at quantifying and comparing the benefits and costs of information sharing across multiple stages of a supply chain and the first to assess quantitatively the role played by information quality and quantity in generating costs and benefits.

To provide a selective bibliography for researchers and practitioners interested in database modeling of engineering information with sources which can help them develop engineering information systems.

Identifies the requirements for engineering information modeling and then investigates how current database models satisfy these requirements at two levels: conceptual data models and logical database models.

Presents the relationships among the conceptual data models and the logical database models for engineering information modeling viewed from database conceptual design.

Currently few papers provide comprehensive discussions about how current engineering information modeling can be supported by database technologies. This paper fills this gap. The contribution of the paper is to identify the direction of database study viewed from engineering applications and provide a guidance of information modeling for engineering design, manufacturing, and production management.

Performance measurement (PM) of any supply chain is prerequisite for improving its competitiveness and sustainability. This paper develops a framework for supply chain performance measurement (SCPM) for agriculture supply chain (ASC) based on internet of things (IoT). Moreover, this article explains the role of IoT in data collection and communication (SC visibility) based on the supply chain operation reference (SCOR) model.

This research identifies various key performance indicators (KPIs) and also their role in SCPM for improving its sustainability by using SCOR. Further, Shannon entropy is utilized for weighing the basic processes of SCPM and by using weights, fuzzy TOPSIS is applied for ranking of identified KPIs at metrics level 2 (deeper level).

“Flexibility” and “Responsiveness” have been reported as two most important KPIs in IoT based SCPM framework for ASC towards achieving sustainability.

In this research, metrics are explained only at SCOR level 2. But, this research will guide the managers and practitioners of various organizations to set their benchmark for comparing their performance at different levels of business processes. Further, this paper has managerial implications to develop an effective system for PM of IoT based data-driven ASC.

By using IoT based data driven system, this article fills the gap between SCPM by measuring different SC strategies in their performance measurable form of reliable, responsive and asset management etc.

The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.