Exploring and visualizing spatial-temporal evolution of patent collaboration networks: A case of China's intelligent manufacturing equipment industry

With the integration of intelligent manufacturing (IM) technology and the manufacturing industry, the intelligent manufacturing equipment industry (IMEI) has become the focus of a new round of industrial revolution. This integration has led to a new revolution in the manufacturing industry and is key to transforming China into a manufacturing country with international competitiveness. However, China's IMEI is in the development stage, thus presenting a major challenge to it becoming a competitive core industry. Therefore, there is an urgent need to explore the IMEI patent collaboration network and analyze its evolutionary characteristics, which can improve not only the innovation ability of network organizations but also the overall competitiveness of the IMEI. This study employs social network analysis (SNA) to study the evolution of the patent collaboration network of China's IMEI. The results show that the number of co-patents for the IMEI field in China has obvious stage characteristics, the collaborative innovation patterns adopted by different provinces vary, and the State Grid has a strong influence on the network. The scale of the patent collaboration network is gradually expanding, exhibiting a “small-world” structure. Jiangsu mainly innovates through intra-provincial collaboration. Provinces such as Beijing, Guangdong and Shandong are more inclined to inter-provincial collaboration.     

Product platform architecture for cloud manufacturing

Cloud manufacturing is emerging as a new manufacturing paradigm and an integrated technology. To adapt to the increasing challenges of the traditional manufacturing industry transforming toward service-oriented and innovative manufacturing, this paper proposes a product platform architecture based on cloud manufacturing. Firstly, a framework for the product platform for cloud manufacturing was built. The proposed architecture is composed of five layers:resource, cloud technology, cloud service, application, and user layers. Then, several key enabling technologies for forming the product platform were studied. Finally, the product platform for cloud manufacturing built by a company was taken as an application example to illustrate the architecture and functions of the system. The validity and superiority of the architecture were verified.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00306-1     

A novel cloud manufacturing service composition platform enabled by Blockchain technology

In the near future, manufacturing industries will be mostly recognised with characteristics like IoT, and massive data transactions. To fulfil these characteristics, paradigms like Cloud manufacturing, Industry 4.0 and smart factory have passed their preliminary steps to become the primary inspirations. Considering the nature of Cloud manufacturing which consists of a vast number of service providers and Service demanders being introduced to the manufacturing cloud, service composition problem is introduced. However, there is a big challenge for fulfilling the dynamic behaviour of parameters which change rapidly over time in the service composition problem. This paper challenges the centralised mechanism of service composition problem and introduces a novel platform entitled Blockchain-based service composition model (Block-SC) based on the Blockchain technology. Block-SC as a novel manufacturing architecture conquers the centralised mechanism by dividing the original service composition problem into multiple sub-problems each of which contains a small fraction of the service/task pool. The capabilities of the proposed platform are remarkable from two perspectives; first, it provides an effective mechanism for collaboration of service composition service providers with a service-oriented approach and from the second perspective, the optimality of service composition problem is profoundly affected considering the dynamic behaviour of Cloud manufacturing.     

Management of sustainable manufacturing systems-a review on mathematical problems

The ever-growing awareness of environmental protection has significantly influenced the method of manufacturing products. Due to the introduction of new processes, the management of sustainable manufacturing shows different characteristics to those of traditional systems. Sustainable manufacturing systems have attracted a great deal of attention in the past 20 years as an emerging manufacturing approach. Particularly in the last 10 years, the number of papers focusing on the topic of sustainable manufacturing systems’ management has increased rapidly. More and more practical factors have been considered and integrated into this area which makes it more complex, but closer to reality. This paper aims to classify the mathematical problems dealing with the management of sustainable manufacturing systems. More than 100 related papers mainly from 1994 to 2015 have been selected and reviewed and divided into three categories according to the main elements in a manufacturing system: production planning and control, inventory management and control and manufacturing network design. The development of each category is summarised and the corresponding mathematical problems are discussed to provide a general overview of the relevant research fields and identify future research directions.     

A novel model for optimisation of logistics and manufacturing operation service composition in Cloud manufacturing system focusing on cloud-entropy

In recent years, economic globalisation and manufacturing resource globalisation as two key factors have driven enterprises to transform their business processes to survive in competitive environments. This transformation is challenging as manufacturing enterprises should maintain their support for their customers with high-quality products, lower cost, product customisation capabilities, and quick delivery. Moreover, globalisation has resulted in geographically distributed suppliers across the globe. This challenge will turn into a major research topic when paradigms like Cloud manufacturing are introduced. Cloud manufacturing is a new paradigm which provides ubiquitous, convenient, on-demand network access to a shared pool of configurable manufacturing resources. In this paper, to achieve the ideal goal of Cloud manufacturing, the concept of supplier network logistics planning and manufacturing service composition is focused. Every production task and logistics operation would be defined as a service considering operation process chart flows. The paper has proposed a mathematical model which selects an optimal set of manufacturing and logistics service composition in order to lower operation and logistics costs in operational perspective while fulfilling a novel idea for configured cloud entropy of logistics and operation suppliers. Finally, the paper has presented a numerical example and concluded the remarks, and outlined future research.     

云制造中产品个性化定制研究综述

消费者对个性化产品购买需求的增加,对制造企业的定制生产能力提出了越来越高的要求。而现有制造企业存在的信息化水平不高、制造资源不足等问题,严重影响了制造企业向个性化生产转型的进程。针对上述情况,结合云制造概念及技术提出了云制造中产品个性化定制生产模式。为了更加深入地研究云制造中产品个性化定制的运行模式及阐述云制造平台在定制生产过程中的主要作用,从体系架构、服务流程、关键技术等方面对相关研究进行了回顾和介绍,然后列举了个性化定制生产模式在汽车、软件和服装行业的应用,最后对研究趋势进行了展望。分析表明,云制造平台汇聚全球的制造资源为个性化定制服务,能够有效解决单一制造企业实施个性化定制过程中面临的一系列困难,做到以较低的成本快速高效地满足消费者日益多样化、个性化的需求。     

Ecosystem evolution mechanism of manufacturing service system driven by service providers

To date, research has mainly discussed the definition and classification of producer services. Yet many companies require an integrated solution of products and producer services. The aim of this paper is to propose a model of the ecological evolution of manufacturing service systems (MSS) driven by service providers. This model adopts modular thinking to integrate dispersive producer services into an entire MSS, the process of which forms the ecological evolution of MSS. This paper applies ecological theory to build the ecological evolution mechanism of MSS. In this mechanism, the predator–prey relationship is used as a metaphor for the relationships between manufacturers and service providers in a MSS. A predator–prey model is built to simulate the ecological evolution of MSS. A predation cellular genetic algorithm is adopted to optimise this evolution. The proposed model and algorithm are demonstrated and validated by a case study of MSS in bicycle industry. This study contributes to theory by proposing and clarifying the mechanism for provision of services between businesses. The future research will focus on the application and empirical analysis of this mechanism derived from big data.     

Influence of maintenance policies on multi-stage manufacturing systems in dynamic conditions

Manufacturing systems are subject to a degradation process that leads to machine failure if no action is taken. Machine failures reduce the performance of the manufacturing system with loss of profits. The research proposed here concerns the evaluation of the manufacturing system performance in dynamic conditions when different maintenance policies are implemented in a multi-machine manufacturing system controlled by multi-agent-architecture. There are two extreme maintenance policies that can be applied: no preventive maintenance, where action is taken on the failure state, and intensive preventive maintenance, which can eliminate unforeseen failures, but at a high cost. Dynamic policy maintenance is proposed to reduce the number of maintenance operations of the preventive policy. A discrete simulation environment has been developed in order to investigate the performance measures and the indexes of the costs of maintenance policies. The simulations have been conducted for several levels of mix, product demand and working time uncertainty. The simulation results show that the proposed approach leads to better performance for the manufacturing system and reduces the number of maintenance operations (cost index of the maintenance policy), except in the case of the mean time between failure, which is characterised by a very low standard deviation.     

Scheduling policies in multi-product manufacturing systems with sequence-dependent setup times and finite buffers

Multi-product production systems with sequence-dependent setup times are typical in the manufacturing of semiconductor chips and other electronic products. In such systems, the scheduling policies coordinating the production of multiple product types play an important role. In this paper, we study a multi-product manufacturing system with finite buffers, sequence-dependent setup times and various scheduling policies. Using continuous-time Markov chain models, we evaluate the performance of such systems under seven scheduling policies, i.e. cyclic, shortest queue, shortest processing time, shortest overall time (including setup time and processing time), longest queue, longest processing time, and longest overall time. The impacts of these policies on system throughput are compared, and the conditions characterising the superiority of each policy are investigated. The results of this work can provide production engineers and supervisors practical guidance to operate multi-product manufacturing systems with sequence-dependent setups.     

Assessing manufacturing strategy definitions utilising text-mining

The variations in Manufacturing Strategy (MS) definitions create confusion and lead to lack of shared understanding between academic researchers and practitioners on its scope. The purpose of this study is to provide an empirical analysis of the paradox in the difference between academic and industry definitions of MS. Natural Language Processing (NLP) based text mining is used to extract primary elements from the various academic, and industry definitions of MS. Co-word and Principal Component Analysis (PCA) provide empirical support for the grouping into nine primary elements. We posit from the terms evolution analysis that there is a stasis currently faced in academic literature towards MS definition while the industry with its emphasis on ‘context’ has been dynamic. We believe that the proposed approach and results of the present empirical analysis can contribute to overcoming the current challenges to MS design and deployment – imprecise definition leading to its inadequate operationalisation.     

Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS

It is of great practical significance to optimise the decision-making of cloud manufacturing service providers, which can ensure the efficient operation of the cloud manufacturing services. In order to effectively optimise, this paper constructs the evaluation index system, sorts out 7 important evaluation indexes. A method is proposed on the basis of the TOPSIS method and Grey Correlation Analysis (GRA), which is a decision-making method combining static distance and dynamic trend, and make the evaluation results more reasonable. In addition, in order to reflect the true weight of the high dimensional index, the evaluation model of projection pursuit index is established. The improved Particle Swarm Optimisation (PSO) algorithm is used to optimise the projection index function and model parameters, and to obtain the objective weights of evaluation indexes. Then the objective weights combine with the subjective weights obtained by the Analytic hierarchy process (AHP), which makes the weights of the evaluation indexes achieve the unity of subjective and objective. Finally, 20 sets of simulation examples are given to illustrate the feasibility and effectiveness of the proposed method.     

面向制造过程的装配公差模型研究

为了研究零件制造偏差对装配公差的影响,提出了一种面向制造过程的装配公差模型.基于小位移矢量方法建立零件表面公差模型,采用齐次坐标变换方法描述偏差累积,建立了工艺系统各组件的装配公差模型.在满足装配约束条件的前提下,考虑了装配零件的几何变动,利用统计法研究装配体的装配成功率.最后应用一实例对装配体进行了公差分析,验证了模型的合理性.该模型可以用于指导装配规划,避免不可装配性.     

Competitive and sustainable manufacturing by means of ultra-efficient factories in urban surroundings

The rapid growth of the world population, the finiteness of resources on our planet Earth and the ongoing tendency towards urbanisation result in the need to question our actions and economic activities, also for industrial enterprises. A paradigm shift to decouple growth and resource utilisation is needed. By means of ultra-efficiency, factories are targeted, whose positive impact to their surrounding is optimised instead of only minimising negative influences. In the contribution, the concept of ultra-efficient factories and first tools for their implementation are introduced. Therefore, the term ultra-efficient factory is defined based on the state of the art. On this definition, spheres of activity for ultra-efficient factories under consideration of urban surroundings are determined. For the spheres of activity, criteria to assess the according maturity of companies are identified and aggregated into a comprehensive maturity model. The maturity model enables the determination of potentials for advancements of companies. To support the industrial application of the theoretic work, industrial best practices are determined and a visual tool is developed.     

The policy trajectory of dual-use technology integration governance in China: A sequential analysis of policy evolution

Promoting research, development, and application of dual-use technologies contributes to the coordinated achievement of national security and economic growth. Dual-use technology integration (DTI) governance is a transformation that promotes technology transfer across defense and civil systems. This study employed a policy evolution sequential analysis paradigm based on the dynamic evolution of policy mixes. The policy trajectory of DTI governance in China was examined from the perspective of socio-technical system transitions. Five main findings were identified. (1) Policy evolution has been affected by both endogenous and exogenous factors. (2) The core policy-issuing agencies have steadily transitioned from specialized to comprehensive agencies, and the complexity of the joint policy-issuing network has grown. (3) Policy targets coexist; however, the emphasis at each stage differs. (4) DTI policy mixes follow changes in key policy targets. (5) Policy topics undertake and complement previous and subsequent stages. Practical and theoretical contributions to dual-use technology, socio-technical system transition, and policy evolution are presented. Furthermore, we propose that future research be conducted to identify the common traits of policy evolution across nations or fields.     

Impact of sustainable manufacturing practices on consumer perception and revenue growth: an emerging economy perspective

The view that adopting an environmental perspective on operations can lead to improved operations has become commonplace over the past decade. The implication is that any operational system that has minimised inefficiencies is also more environmentally sustainable. In the first phase of our research, we conducted a field research of the green manufacturing techniques in place in two world-class, ISO 14001-certified paint manufacturing firms in India. This phase of the study was undertaken to ascertain the cost benefits that these firms enjoy due to green manufacturing and recycling. Based on the field work in these two companies, a conceptual framework was proposed to investigate any relationship between the consumer's attitude towards the environment and the perceived image of a company that was environmentally conscious. Subsequently, a survey was administered to understand the impact of green marketing on the decision of consumers to buy paint manufactured by a firm that stringently regulates its hazardous waste. Results indicate that there is a strong correlation between the environmental concern of the survey respondent and the perception that the respondent forms of the firm that has implemented green manufacturing techniques. There is also a strong correlation between the decision to buy a green product and the respondent's concern for the environment as well as the perception formed of the firm. Further research is required to substantiate the cost benefits of green manufacturing.     

Cloud manufacturing resources fuzzy classification based on genetic simulated annealing algorithm

To solve the problem of fuzzy classification of manufacturing resources in a cloud manufacturing environment, a hybrid algorithm based on genetic algorithm (GA), simulated annealing (SA) and fuzzy C-means clustering algorithm (FCM) is proposed. In this hybrid algorithm, classification is based on the processing feature and attributes of the manufacturing resource; the inner and outer layers of the nested loops are solving it, GA obtains the best classification number in the outer layer; the fitness function is constructed by fuzzy clustering algorithm (FCM), carrying out the selection, crossover and mutation operation and SA cooling operation. The final classification results are obtained in the inner layer. Using the hybrid algorithm to solve 45 kinds of manufacturing resources, the optimal classification number is 9 and the corresponding classification results are obtained, proving that the algorithm is effective.     

基于搅拌摩擦的金属固相增材制造研究进展EI北大核心CSCD

基于搅拌摩擦的固相增材制造是大型轻质合金构件成形制造的新技术,已成为国内外先进成形制造领域研究的热点之一。本文对目前国内外基于搅拌摩擦的金属固相增材制造技术及其相关工艺机理的研究现状进行了分析和总结。常见的基于搅拌摩擦的固相增材制造技术可分为三类:基于搅拌摩擦搭接焊原理,使板材逐层堆积,从而获得增材构件的搅拌摩擦增材制造(friction stir additive manufacturing,FSAM)技术;采用中空搅拌头,通过添加剂(粉末或丝材)进行固相搅拌摩擦沉积的增材制造(additive friction stir deposition,AFSD)技术;采用消耗型棒材,通过棒材的摩擦表面处理,形成增材层的摩擦表面沉积增材制造(friction surfacing deposition additive manufacturing,FSD-AM)技术。重点分析了金属材料基于搅拌摩擦的固相增材制造技术的国内外研究与应用现状,对比了三类基于搅拌摩擦的固相增材制造技术的特征及其工艺优缺点。最后指出增材工艺机理、形性协同控制、外场辅助工艺改型、新材料应用和人工智能优化是基于搅拌摩擦的固相增材制造技术未来研究的重点方向。     

Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms

Several efficient pull production control policies for serial lines implementing the lean/JIT manufacturing philosophy can be found in the production management literature. A recent development that is less well-studied than the serial line case is the application of pull-type policies to assembly systems where manufacturing operations take place both sequentially and in parallel. Systems of this type contain assembly stations where two or more parts from lower hierarchical manufacturing stations merge in order to produce a single part of the subsequent stage. In this paper we extend the application of the Base Stock, Kanban, CONWIP, CONWIP/Kanban Hybrid and Extended Kanban production control policies to assembly systems that produce final products of a single type. Discrete-event simulation is utilised in order to evaluate the performance of serial lines and assembly systems. It is essential to determine the best control parameters for each policy when operating in the same environment. The approach that we propose and probe for the problem of control parameter selection is that of a genetic algorithm with resampling, a technique used for the optimisation of stochastic objective functions. Finally, we report our findings from numerical experiments conducted for two serial line simulation scenarios and two assembly system simulation scenarios.     

Collaboration of large equipment complete service under cloud manufacturing mode

This paper focuses on the need of the large equipment manufacturing industry to adapt collaborative operation to transform the industry to cloud manufacturing services and to solve the new problem of federal resources coordination in complete service operation. We systematically study federal resources cooperation under cloud manufacturing mode to complete a large complex project. The primary research contents are divided into four points. First, a system structure of cloud manufacturing service mode is presented. Second, a synergy logic framework from the global system perspective is designed based on generalised partial global planning. Third, a multi-level system coordination mechanism is established by integrating various methods, including the bidding game mechanism for enterprise external resources, the planning control mechanisms for enterprise internal resource and the global collaborative optimisation mechanism for enterprise global federal resources. Finally, a cloud manufacturing service platform for a typical enterprise is developed by combining theory with practice. The results can realise collaborative management in resource selection and configuration, service process planning control and service information feedback in cloud manufacturing service, as well as achieve overall synergy effect for the system.     

Reliability analysis of a flexible manufacturing cell

In this study, mathematical models are developed to study and compare the operations of a fully reliable and an unreliable flexible manufacturing cell (FMC), each with a flexible machine, a loading/unloading robot, and a pallet handling system. The operation times, loading/unloading times, and material handling times by the pallet are assumed to be random. The operation of the reliable cell is compared to that of an unreliable cell with respect to utilization of the cell components, including the machine, robot, and pallet handling system. The unreliable cell is assumed to operate under random (machine and robot) failures with constant failure rates for the machine and the robot. The pallet handling system is assumed to be completely reliable.