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Since the data model plays an important role in designing manufacturing execution system (MES) database, this paper seeks to provide a generic and adaptable data model for MES, which can facilitate and improve the MES development.

Extended entity‐relationship (EER) model technique is adopted to build the data model of MES.

Based on MES functions and database requirement analysis, four subject's structures of MES database is abstracted from a system integration point of view. These four structures are independent relatively but also have close interrelation. Each structure is modeled with EER model.

The presented data model mainly focuses on discrete manufacturing MES, which perhaps limits its usefulness elsewhere, and the data model still need further testing in manufacturing enterprises with different scales.

A prototype MES system is developed and implemented, the results show that the proposed EER modeling approach can establish and make clear complex relationships among entities existed in a manufacturing system, which lays the foundation for adaptable and modular MES software development and implementation.

This paper fulfils a fundamental need of designing data model for MES and provides a main framework for developing MES data model, which provides reference for researches both in academia and industry to build specific relational data models for specific needs.

This paper aims to develop a service‐oriented distributed multi‐robot system based on manufacturing message specification (MMS) and new‐generation distributed object technology – web services for realizing remotely monitoring and controlling multiple heterogeneous robots in the internet environment.

The study presents robot communication model and distributed multi‐robot monitoring and control software structure based on MMS and web services. In particular, monitoring and control software design of MMS concepts in web services environment using Unified Modeling Language model is discussed in detail. In addition, to verify the validity of the proposed design method, a multi‐robot prototype system for robot flexible assemble cell has been achieved. Its Server software is implemented in C++ with Visual Studio.NET being the development environment and Client software is programmed in Java with Borland JBuilder 9 being the development tool.

Finds that the communication structure following MMS can make the multi‐robot monitoring and control system have perfect robustness, interoperability and reconfigurability. Besides, web services technology can conveniently realize MMS services, also can successfully resolve the remote multi‐robot monitoring and control problem among cross‐network, cross‐platform and heterogeneous systems.

Provides an easy and low‐cost method for realizing heterogeneous multi‐robot remote driving. The web‐based distribution of the presented system is critical in enabling capabilities such as e‐manufacturing, e‐diagnostics and e‐maintenance.

The proposed system can be seamlessly integrated into other automated manufacturing systems or management systems in plug‐and‐play fashion. The combination of MMS and web services is in favor of real manufacturing equipments being embedded in the network, so the presented systematic methodology can be a useful reference for constructing web‐based reconfigurable manufacturing systems.

Provides robot communication model based on MMS and web services and presents service‐oriented distributed remote multi‐robot monitoring and control software architecture.

The promotion of new energy vehicles (EVs) is an effective way to achieve low carbon emission reduction. This paper aims to investigate the optimal pricing of automotive supply chain members in the context of dual policy implementation while considering consumers' low-carbon preferences.

This article takes manufacturers, retailers and consumers in a main three-level supply chain as the research object. Stackelberg game theory is used as the theoretical guidance. A game model in which the manufacturer is the leader and the retailer is the follower is established. The author also considered the impact of carbon tax policies, subsidy policies and consumer preferences on the results. Furthermore, the author investigates the optimal decision-making problem under the profit maximization model.

Through model solving, it is found that the pricing of EVs is positively correlated with the unit price of carbon and the amount of subsidies. The following conclusions can be obtained by numerical analysis of each parameter. Changes in carbon prices have a greater impact on conventional gasoline vehicles. Based on the numerical analysis of parameter β, it is also found that when the government subsidizes consumers, supply chain members will increase their prices to obtain partial subsidies. Compared with retailers, low-carbon preferences have a greater impact on manufacturers.

The new energy automobile industry involves many policies, including tax cuts, tax exemptions and subsidies. The policy environment faced by the members of a supply chain is complex and diverse. Therefore, the analysis in this article is based only on partial policies.

The authors innovatively combine the three factors of subsidy policy, carbon tax policy and consumer low-carbon preference, with research on the pricing of EVs. The influence of policy factors and consumer preferences on the pricing of EVs is studied.

Despite most studies on political ties focusing on the interpersonal relationships between firms and government officials, this study suggests that local party committees (LPCs) create special forms of political ties in China – i.e. organizational political ties. The purpose of this paper is to examine the influences that these organizational political ties have on Chinese firms’ innovative activities.

Drawing upon data based on a nationwide survey of Chinese firms in 2013, this study uses a structural equations model to examine the relationship between LPCs and firms’ innovations.

This study found that LPCs do affect firms’ innovations positively, including both radical innovations and incremental innovations.

By suggesting that LPCs are a form of political tie particular to China – i.e. an organizational political tie – this study’s findings may shed fresh light on the research into political ties in other emerging economies.

Compared to traditional political ties, maintaining the organizational political ties fostered by LPCs benefits firms’ innovations significantly in China, making them less costly and more stable.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

The wavelet neural network (WNN) has the drawbacks of slow convergence speed and easy falling into local optima in data prediction. Although the artificial bee colony (ABC) algorithm has strong global optimization ability and fast convergence speed, it also has the drawbacks of slow speed while finding the optimal solution and weak optimization ability in the later stage.

This article uses an ABC algorithm to optimize the WNN and establishes an ABC-WNN analysis model. Based on the example of the Jinan Yuhan underground tunnel project, the deformation of the surrounding rock of the double-arch tunnel crossing the fault fracture zone is predicted and analyzed, and the analysis results are compared with the actual detection amount.

The comparison results show that the predicted values of the ABC-WNN model have a high degree of fitting with the actual engineering data, with a maximum relative error of only 4.73%. On this basis, the results show that the statistical features of ABC-WNN are the lowest, with the errors at 0.566 and 0.573, compared with the single back propagation (BP) neural network model and WNN model. Therefore, it can be derived that the ABC-WNN model has higher prediction accuracy, better computational stability and faster convergence speed for deformation.

This article uses firstly the ABC-WNN for the deformation analysis of double-arch tunnels. This attempt laid the foundation for artificial intelligence prediction in deformation analysis of multi-arch tunnels and small clearance tunnels. It can provide a new and effective way for deformation prediction in similar projects.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

The purpose of this paper is to recommend a framework for remodelling a public sector knowledge management system (KMS) using key knowledge management (KM) processes. The rationale is to provide insight and guidelines to organisations that struggle with KM.

This desktop study adopted the qualitative approach and literature to support the understanding regarding the remodelling of the public sector KMS using key KM processes.

The study found that if KM processes are not considered, the prospect of KM is limited. The best way to manage public sector knowledge is following KM processes using information technology. Without proper KM, organisations may not know how knowledge is generated, codified, stored, shared and used in an organisation.

The paper provides a framework to guide public sector organisations in the implementation of electronic KM. Thus, proposing a new way of managing knowledge by using the electronic KM processes in the public sector organisations. The study will also benefit other organisations implementing KM programmes.