六盘水市煤炭行业竞争战略分析

我国是富煤贫油少气的国家，煤炭是我国最重要的一次能源。但从能源激烈的竞争市场环境而言，当前我国煤炭行业发展出现了困境。为了更好地发展六盘水地区的煤炭行业，结合竞争战略理论和六盘水市的煤炭行业发展状况，运用PEST分析法和波特五力模型对六盘水市煤炭行业进行分析，得出整合资源，结合自身优势大力吸引人才，最终达到产业转型的生态化煤炭发展战略模型。分析结果可为提高六盘水煤炭行业竞争力提供理论支持。     

Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.     

The co-location of innovation and production in clusters

ABSTRACT

This paper quantifies the extent of co-location of innovation and production for industry clusters with varying knowledge intensity. If input-output, knowledge, and skill linkages are interdependent and geographically bounded, then we would expect innovation and production to be co-located in regional clusters. However, theory predicts that the degree of agglomeration benefits associated with co-location may vary across economic activities with different knowledge intensity. Using data from the U.S. Cluster Mapping Project, I develop measures of the co-location of innovation and production for 27 industry clusters, examining patterns across regions and over time (1998–2015) in the United States. I find that there is a significant co-location of innovation and production for many clusters, especially for those with higher knowledge intensity. This paper focuses on the Information Technology and Analytical Instruments cluster and the Automotive cluster to illustrate the co-location measures and the micro-geography of innovation and production.     

Cloud based cyber-physical systems: Network evaluation study

In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers’ locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency. The most significant impact lies in the data center distance and the speed of the communication channel. Moreover, the communication protocol also has impact on the latency. The feasibility of controlling each level of RAMI 4.0 through cloud services was investigated. Experimental results showed that control is possible in many solutions, but these solutions mostly cannot depend just on cloud services. The intelligence on the edge of the network will play a significant role. The main contribution is a thorough evaluation of different cloud providers, locations, and communication protocols to provide recommendations sufficient for different levels of the RAMI 4.0 architecture.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Ageing workforce management in manufacturing systems: state of the art and future research agenda

The workforce ageing phenomenon is recently affecting most of the Organisation for Economic Co-operation and Development (OECD) member countries, due to a general ageing of their populations and a higher average retirement age of the workforce. In this paper, the topic of ageing workforce management is addressed from a production research standpoint, with the aim of understanding how older workers can be supported and involved in a manufacturing system. First, the current state of the art related to the ageing workforce in production systems is presented. This is structured according to four main topics: (1) analysis and evaluation of ageing workers’ functional capacities, (2) consideration of ageing workers’ capacities in industrial system modelling and management, (3) analysis and exploitation of ageing workers’ expertise, (4) acknowledgement, analysis, design and integration of supporting technologies. Next, the discussion on the impact of the ageing workforce on manufacturing systems’ performances leads to the comparison of some technological advances that are related to the Industry 4.0 paradigms. Finally, a future research agenda on this topic is proposed, based on the same topics classification proposed for the literature analysis. Five different research areas are derived, suggesting future directions for appropriate research concerning the employ of older workers in production environments.     

Development of a procedure writers’ guide framework: Integrating the procedure life cycle and reflecting on current industry practices

The current study aims to advance a procedure development process that will create procedures as effective safeguards. Several past incidents identified that many current procedural systems failed to support workers conducting their work safely and effectively. There is currently a dearth of systematic inquiry regarding the procedure development process. A key element of the procedure development process is writers' guide, which dictates how these procedures should be developed, written, reviewed and managed. The current effort collected 16 writers' guides across various industries such as chemical, oil and gas, nuclear, and energy. Different components of these writers' guides were identified, summarized, and later categorized according to a newly developed writers' guide framework. The framework uses four phases of the procedure life cycle and five sections for procedure content. The analysis showed that industry practices primarily focus on general goals of the procedure, writing style, and review process. Many important components of the procedure, such as process hazard information, execution challenges, and training requirements were not addressed adequately. Of the 41 components, there were only 3 that 80% of the writers' guides contained suggesting little consensus about the content. The proposed writers' guide framework organizes all components including low frequency of appearance ones in different phases of procedure life cycle. The significance of the current procedure writers' guide framework is that it not only produces a structure for a comprehensive writers’ guide but also opens an opportunity for future improvement in current procedure writing practices.     

Symptoms and risks for musculoskeletal disorders among male and female footwear industry workers

BackgroundConsidering the growing participation of woman in the labor market and the high prevalence of the musculoskeletal disorders (MSD) in the footwear industry workers, the aim of this study was to evaluate and compare female and male footwear industry workers in relation to their demographics, occupational characteristics, stress levels, MSD symptoms prevalence, physical activity levels, alcohol and tobacco use.MethodsThe study included 175 female and 182 male footwear industry workers. Data was collected using the Perceived Stress Scale – 10, the Standardized Nordic Questionnaire, the International Physical Activity Questionnaire, the Alcohol Use Disorders Identification Test, and the Fagerstrom test for Nicotine Dependence.ResultsThe female workers were younger, had less time in the company and in the current job. They reported more stress (p = 0.001), had less time for physical activity (p = 0.004), higher prevalence of MSD symptoms in the last 12 months (p = 0.003), and consumed less alcohol (p = 0.006) than the male workers.ConclusionsFemale and male footwear industry workers presented significant differences in their demographics, occupational characteristics, stress levels, MSD prevalence, physical activity levels, alcohol and tobacco use. These differences should be taken into consideration in the implementation of intervention programs for optimum outcomes.Relevance to industryFemale footwear industry workers were more stressed, presented higher prevalence of MSD symptoms, and reported less time for physical activity than male footwear industry workers. The differences between male and female workers should be taken into consideration in the implementation of MSD prevention programs.     

Human factors and ergonomics in manufacturing in the industry 4.0 context – A scoping review

Industry 4.0 revolution has brought rapid technological growth and development in manufacturing industries. Technological development enables efficient manufacturing processes and brings changes in human work, which may cause new threats to employee well-being and challenge their existing skills and knowledge. Human factors and ergonomics (HF/E) is a scientific discipline to optimize simultaneously overall system performance and human well-being in different work contexts. The aim of this scoping review is to describe the state-of-the-art of the HF/E research related to the industry 4.0 context in manufacturing. A systematic search found 336 research articles, of which 37 were analysed utilizing a human-centric work system framework presented in the HF/E literature. Challenges related to technological development were analysed in micro- and macroergonomics work system frameworks. Based on the review we frame characteristics of an organisation level maturity model to optimize overall sociotechnical work system performance in the context of rapid technological development in manufacturing industries.     

Scientific mapping to identify competencies required by industry 4.0

The objective of this study was to identify what competencies are identified in the literature as necessary for Industry 4.0 by conducting a survey of the literature and a scientific mapping of the evolution of the issues related to the qualification of professionals for Industry 4.0 and possible paths for research and education. A search was conducted on the Scopus, Web of Science and Science Direct databases for the interval from 2010 to 2018. This systematic review revealed topics and authors currently specialized in the field and allowed mapping the field of study. The identification of journals and keywords useful in future studies was also an object of this study. SciMAT software was used for the systematic literature review. The results are highlighted by the set of competencies (knowledge and skills) that must be developed in professional education to accompany the new industrial revolution, as well as the importance of integrating efforts by companies, governments and universities. These efforts should focus on creating “learning factories”, which are understood to be environments that provide practical experiences to these professionals, preparing them in the best way possible for the requirements of Industry 4.0. This conceptual map showed that the main competencies needed include skills: (leadership, strategic vision of knowledge, self-organization, giving and receiving feedback, pro-activity, creativity, problem solving, interdisciplinarity, teamwork, collaborative work, initiative, communication, innovation, adaptability, flexibility and self-management) and knowledge of contemporary fields (information and communication technology, algorithms, automation, software development and security, data analysis, general systems theory and sustainable development theory).