Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries. Motivated by the major development strategies and needs of industrial intellectualization in China, this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization, as well as their application to smart industrial engineering. First, this study describes a general methodology for the fusion of data analytics and optimization. Then, it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing. Finally, it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization. The framework uses data analytics to perceive and analyze industrial production and logistics processes. It also demonstrates the intelligent capability of planning, scheduling, operation optimization, and optimal control. Data analytics and system optimization tech-nologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing, resources and materials, energy, and logistics systems, such as high energy consumption, high costs, low energy efficiency, low resource utilization, and serious environmental pollution. The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency. Therefore, industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.
The construction industry is facing a gradual but important transformation toward more productivity and collaboration. In this framework, two major approaches are often cited in the literature as having the potential to improve the practices in the industry: Building Information Modeling (BIM) and Lean Construction. Several scientific studies have demonstrated the synergy of these two approaches and very recent research has reported positive results from the use of software applications as support for their implementation on construction sites. However, the stakes of such integration have been very little studied. This article presents the results of a research project conducted within a general contractor firm that decided to implement BIM and Last Planner System (LPS) on its construction sites. The research uses a four-stage action research approach, including the characterization of the research issue, the establishment of an action plan, its implementation and its evaluation. Compared to recent related studies, the research is less enthusiastic. While it highlights the need for new tools to improve production planning and control, it also points to a strong resistance to change by practitioners at the site. They emphasize the necessity for adequate pre-service training and the need for new resources that can work full-time on the ongoing training of site teams. In addition, some limitations of the tool lead workers to believe that it can quickly become a factor that slows down their daily work rather than improving it. Based on the advice of professionals, the paper formulates some recommendations to the industry, the researchers and the software developers.
Energy development concerns not only the development of renewable energies but also the shift from centralised to clean, decentralised power generation. The development of decentralised energy (DE) is a core part of the energy and economic strategies being adopted around the world that drives the progress toward a highly sustainable future. This paper reviews the concepts, development status, trends, benefits and challenges of DE systems and analyses the existing models and methods for assessing the performance of these systems. A hierarchical decision model for evaluating the performance of DE systems is also constructed based on the framework of multiple criteria decision analysis, which considers the identification, definition and assessment grade of decision criteria. The evidential reasoning approach is applied to aggregate assessment information in a case study of the implementation of an intelligent decision system. Sensitivity and trade-off analyses are also conducted to show how the proposed model can be used to support decision making in DE systems.
The field of engineering management usually involves evaluation issues, such as program selection, team performance evaluation, technology selection, and supplier evaluation. The traditional self-evaluation data envelopment analysis (DEA) method usually exaggerates the effects of several inputs or outputs of the evaluated decision-making unit (DMU), resulting in unrealistic results. To address this problem, scholars have proposed the cross-efficiency evaluation (CREE) method. Compared with the DEA method, CREE can rank DMUs more completely by using reasonable weights. With the extensive application of this technique, several problems, such as non-unique weights and non-Pareto optimal results, have arisen in CREE methods. Therefore, the improvement of CREE has attracted the attention of many scholars. This paper reviews the theory and applications of CREE, including the non-uniqueness problem, the aggregation of cross-efficiency data, and applications in engineering management. It also discusses the directions for future research on CREE.
The low carbon energy transition has attracted worldwide attention to mitigate climate change. Renewable energy (RE) is the key to this transition, with significant developments to date, especially in China. This study systematically reviews the literature on RE development to identify a general context from many studies. The goal is to clarify key questions related to RE development from the current academic community. We first identify the forces driving RE development. Thereafter, we analyze methods for modeling RE developments considering the systematic and multiple complexity characteristics of RE. The study concludes with insights into the target selection and RE development roadmap in China.
Servitization of manufacturing has become one of the main pathways for transition and upgrade in the manufacturing industry. New information and communication technologies (ICTs), such as the Internet of Things, Big Data, and Cloud Computing have enabled the servitization of manufacturing in terms of value creation, resource management, and supply chain management. This study presents a comprehensive review on the servitization in operations management in the era of new ICTs. A new value chain framework is proposed under the business model that revolves around servitization, which showcases the new activities and ways of implementation in the era of new ICTs. The virtualization, configuration, and evaluation of integrated manufacturing and service resources are analyzed. In particular, the methods used in new ICT-supported resource management platforms are surveyed. Problems in the supply chain management in manufacturing services (including the selection of partners, as well as the coordination, planning, and scheduling among members) are presented. This study concludes with a discussion on state-of-the-art servitization in operations management in the era of new ICTs.
This multiple case study of a contracting firm contributes to understanding the barriers that organizations face during the implementation of building information modeling (BIM) by providing insights into the impact of these barriers across different organizational levels (i.e., from top management to project teams) and by relating these barriers to different degrees of BIM maturity. First, we observe the dominance of barriers related to the motivation, competence, and time capacity of people across all levels of an organization. Second, the cluster of barriers at the middle-management level highlights the important role of this level in reducing these barriers. Third, only those cases with a low level of BIM maturity have struggled with lack of top management support, thereby highlighting the importance of such support in achieving BIM maturity growth. High BIM maturity situations are more prone to externally oriented barriers in attempting to further leverage the benefits of BIM. Our study provides insights on where to focus BIM implementation measures and how to enhance organizational BIM maturity.
Mega projects require large funding, which often reaches tens or even hundreds of billions of yuan. In the state-oriented financing system, the huge fund gap has generally become an important factor restricting the development of mega projects worldwide. Since the 1980s, China’s long-span bridge projects have developed rapidly as typical mega projects as their financing systems have also undergone a series of changes and shown a high adaptability to complexity. However, the existing literature based on the perspective of evolution lacks focus on the complexity of mega project financing systems and its causes. Therefore, the complexity of the financing methods employed in the financing systems for China’s long-span bridges is analyzed in this work from the dimensions of time and regions through investigation and interviews. On the basis of the results and complex adaptive systems theory, the causes of the complexity are further explored in terms of the clustering effects of financing subjects and the deep uncertainty of financing environments. Then, the evolution rules of financing systems of mega projects are established from the aspect of financing subjects, financing environments, and financing methods. The research results can enrich decision-makers’ understanding of the essential attributes and formation mechanism of the financing systems of mega projects and provide powerful support for decision-making in financing.
Distributed photovoltaic (PV) systems have constantly been the key to achieve a low-carbon economy in China. However, the development of Chinese distributed PV systems has failed to meet expectations because of their irrational profit and cost allocations. In this study, the methodology for calculating the levelized cost of energy (LCOE) for PV is thoroughly discussed to address this issue. A mixed-integer linear programming model is built to determine the optimal system operation strategy with a benefit analysis. An externality-corrected mathematical model based on Shapley value is established to allocate the cost of distributed PV systems in 15 Chinese cities between the government, utility grid and residents. Results show that (i) an inverse relationship exists between the LCOEs and solar radiation levels; (ii) the government and residents gain extra benefits from the utility grid through net metering policies, and the utility grid should be the highly subsidized participant; (iii) the percentage of cost assigned to the utility grid and government should increase with the expansion of battery bank to weaken the impact of demand response on increasing theoretical subsidies; and (iv) apart from the LCOE, the local residential electricity prices remarkably impact the subsidy calculation results.
How latecomers from emerging countries catch up on technological innovation is an important topic for industrial practitioners, policymakers, and academic researchers. This study systematically reviews 37 empirical studies on the precursors of industry catch-up in emerging countries. A general framework on what makes a successful catch-up in latecomer industries is suggested based on literature review. The framework comprises six generic determinants, including technological capability, business ecosystem, government roles, market condition, technological regime, and windows of opportunity. In addition, this framework is applied to the Chinese LED industry, and a case analysis of the catch-up is performed in Chinese LED firms.