Complex Industrial Networks Research Articles

A Subgraph-Based Hierarchical Q-Learning Approach to Optimal Resource Scheduling for Complex Industrial Networks

A Subgraph-Based Hierarchical Q-Learning Approach to Optimal Resource Scheduling for Complex Industrial Networks

Accident spread and risk propagation mechanism in complex industrial system network

Due to the increasing complexity of complex industrial systems, it's indispensable to analyze the process of accident spread and risk propagation on complex systems. An epidemiological model was used to study the phenomena of accident spread and risk propagation in complex industrial systems. It explains the mechanism and pattern of accident spread and risk propagation in complex industrial network, establishes a dynamic model for risk propagation in complex industrial network. The research findings are as follows: (1) In complex industrial systems networks, risk decreases when risk propagation velocity is below a threshold, but it increases and approaches a nonzero equilibrium point when risk propagation exceeds the threshold. (2) The risk propagation threshold is positively linked to information integrity, system robustness, and resilience, while it is negatively associated with the risk preference of management personnel. The risk propagation range decreases as the risk propagation threshold increases. (3) A higher average network degree leads to a higher risk propagation threshold and a smaller risk propagation range. Conversely, network heterogeneity has the opposite effect on the risk propagation threshold and range compared to the average degree. The research conclusions have important theoretical and practical implications for risk management in complex industrial systems.

Study on the characteristics and synergistic effects of industrial complex networks – empirical evidence from Chinese manufacturing

PurposeThe manufacturing industry and the producer service industry have a high degree of industrial correlation, and their integration will cause changes in the complex industrial network topology, which is an important reason for the synergistic effect. This paper describes the topology of industrial systems using complex network theory; further, it discusses how to identify the criticality and importance of industrial nodes, and whether node characteristics cause synergistic effects.Design/methodology/approachBased on the input-output data of China in 2007, 2012 and 2017, this paper constructs the industrial complex network of 30 Chinese provinces and cities, and measures the regional network characteristics of the manufacturing industry. The fixed-effect panel regression model is adopted to test the influence of agglomeration degree and centrality on synergies, and its adjustment mechanism is explored.FindingsThe degree of network agglomeration in the manufacturing industry exerts a negative impact on the synergistic effect, while the centrality of the network exerts a significant promoting effect on the synergistic effect. The results of adjustment mechanism test show that enhancing the autonomous controllable ability of the regional industrial chain in the manufacturing industry can effectively reduce the effect of network characteristics on the synergistic effect.Research limitations/implicationsBased on input-output technology, this paper constructs a complex industrial network model, however, only basic flow data are used. Considerable in-depth and detailed research on the economic and technological connections within the industry should be conducted in the future. The selection of the evaluation index of the importance of industrial nodes also needs to be further considered. For historical reasons, it is also difficult to obtain and process data when carrying out quantitative analysis; therefore, it is necessary to make further attempts from the data source and the expression form of evaluation indicators.Practical implicationsIn a practical sense this has certain reference value for the formulation of manufacturing industrial policies the optimization of regional industrial layout and the improvement of the industrial development level. It is necessary to formulate targeted and specialized industrial development strategies according to the characteristics of the manufacturing industry appropriately regulate the autonomous controllable ability of the industrial chain and avoid to limit the development of industries which is in turn limited by regional resources. Industry competition and market congestion need to be reduced industry exchanges outside the region encouraged the industrial layout optimized and the construction of a modern industrial system accelerated.Social implicationsThe above research results hold certain reference importance for policy formulation related to the manufacturing industry, regional industrial layout optimization and industrial development level improvement. Targeted specialized industrial development strategies need to be formulated according to the characteristics of the manufacturing industry; the autonomous controllability of the industrial chain needs to be appropriately regulated; limitation of regional resources needs to be avoided as this restricts industrial development; and industry competition and market congestion need to be reduced. Agglomeration of production factors and optimization of resource allocation is an important part of a beneficial regional economic development strategy, and it is also an inevitable choice for industrialization to develop to a certain stage under the condition of a market economy. In alignment with the research conclusions, effective suggestions can be put forward for the current major industrial policies. In the process of promoting the development of the manufacturing industry, it is necessary for regional governments to carry out unified planning and guidance on the spatial layout of each manufacturing subsector. Regional governments need to effectively allocate inter-industry resources, better share economies of scale, constantly enhance the competitive advantages and competitiveness of development zones and new districts and promote the coordinated agglomeration and development of related industries with input industries. Industrial exchanges outside the region should be encouraged, the industrial layout should be optimized and the construction of a modern industrial system should be accelerated.Originality/valueComplex network theory is introduced to study the industrial synergy effect. A complex industrial network of China's 30 regions is built and key network nodes are measured. Based on the dimensionality of the “industrial node – industrial chain – industrial complex network”, the research path of industrial complex networks is improved.

Multilevel optimization framework to support self-sustainability of industrial processes for energy/material recovery using circular integration concept

Climate change, resource scarcity, waste reduction, and the lack of sustainability in process industries are vital concerns that civilization confronts. The process integration methodology may aid such sustainability. In this study, a novel chemical exergy resource recovery network is proposed for optimal energy and waste recovery in high-salinity-gradient chemical industries using a pressure-retarded osmosis membrane while indicating a self-sustainability and allocation in complex industrial networks. The mathematical programming paradigm is expressed as a multilevel optimization model to introduce novel ideas for explicitly modeling the trade-offs between waste and energy flows in circular integration while demonstrating industrial network’s environmental impact assessment. This problem is decomposed into two subproblems (SPs) that must be addressed sequentially. The first SP is designed to decrease the total cost of the network while reducing external resource use. The second SP formulates a mixed-integer nonlinear programming model with the objective of minimizing the environmental effects and exergy consumption rate of the network. A case study of a naphthalene-methaforming plant demonstrates the efficacy of the proposed methodology. The results showed that using a tri-level optimization technique, a considerable improvement in flowrate, total annualized cost, and energy recovery is obtained while limiting the network's environmental impact. The operating phase accounts for approximately 75% of the global warming potential output. The proposed tri-level approach based on Benders’ decomposition approach reduced the overall cost of the network by 19.29%, and 47.42 MW net power is recovered in the case study. In addition, the circular exergy use rate and environmental factor were reduced from 400 to 0.037 MW and from 2.569 to 1.481 kgCO2/year, respectively, using the tri-level decomposition approach.

Optimal configuration and economic analysis of PRO-retrofitted industrial networks for sustainable energy production and material recovery considering uncertainties: Bioethanol and sugar mill case study

In this study, an optimal scheme is proposed by utilizing waste streams at a plant-wide scale along with pressure retarded osmosis (PRO) membrane allocation in complex industrial networks for energy recovery. Chemical exergy pinch analysis (ChExPA) and process graph (P-graph) are used to address the problem. The ultimate goals of utilizing the tools are (1) determine the optimal external load consumption, (2) minimizing the waste discharge, and (3) sustainable energy production while utilizing high chemical exergy potential waste discharges. A reliability assessment assisted with Monte-Carlo simulation is further performed to evaluate the proposed solutions from P-graph considering uncertainties. The effectiveness of the proposed methodology is explained using three industrial case studies which covered both intra-plant and inter-plant networks. The results indicated that ChExPA and P-graph can effectively identify the optimal location of the PRO membrane in industrial networks. Upon analyzing the complex inter-plant industrial networks 7.795 MW net power output was harnessed, and significantly higher waste of 384.92 kg/s was recovered with a levelized cost of energy of 0.073 $/kWh. The inter-plant network shows the greatest net profit which accounted for approximately $1,191,000 (i.e., 5.84 times higher than stand-alone plants) with a reasonable payback-period of 4.5 years.

Intelligent deception techniques against adversarial attack on the industrial system

Community detection algorithms (CDAs) are aiming to group nodes based on their connections and play an essential role in the complex system analysis. However, for privacy reasons, we may want to prevent communities or a group of nodes in the complex industrial network from being discovered in some instances, leading to the topics on community deception. In this paper, we introduce and formalize two intelligent community deception methods to conceal the nodes from various CDAs. We used node-based matrices, persistence and safeness scores, to formalize the optimization problems to confound the CDAs. The persistence score is used to destabilize the constant communities in the network while the safeness score is used to assess the level of hiding of a node from CDAs. The objective functions aim to minimize the persistence score and maximize the safeness score of the nodes in the network. From the simulation results, it can be analyzed that the proposed strategies are intelligently concealing the community information in the complex industrial system.

Solving complex retrofit problems using constraints and bridge analysis

The aim of this paper is to conduct retrofit analysis of large, complex industrial Heat Exchanger Networks using an automated Bridge Analysis. Large, complex networks have many different possible retrofit designs, or Retrofit Bridges, which requires both computational effort and user effort to evaluate. In this paper, constraints relating to the thermodynamic and economic performance of a retrofit design are proposed and applied to significantly reduce Retrofit Bridge options to a smaller, manageable number of design options. These constraints relate to capital costs, payback period, piping, and plant layout. The method is demonstrated with a Kraft pulp mill case study. The Kraft pulp mill currently has 54 heat exchangers and 73 hot and cold streams. Without constraints, the number of possible Retrofit Bridges is 1 x 1020. After applying the constraints, this number is reduced to 15. The remaining Retrofit Bridges are considered to provide high thermodynamic and economic benefit and can be more easily assessed for the best projects. The use of constraints has allowed the complex case study to be solved quickly, and a single design can be selected for further development. The suggested design reduces the utility consumption by 9.2 MW and has an annual Total Retrofit Profit of NZD 2,140,000, requiring a single new exchanger.

The motives for Japanese foreign direct investment in the Southeastern United States

PurposeWhereas the USA is still the largest investment destination for Japanese companies, Japan also accounts as the second largest source of investment in the country. The purpose of this paper is to, empirically, examine the detailed motives of Japanese affiliates when investing in the Southeastern USA, adding to previous research at the national level.Design/methodology/approachThis paper uses a qualitative approach based on the interviews of long-term Japanese investors in the manufacturing and wholesale trade industries in the Southeastern USA and applies text analysis to identify their motives.FindingsThe results show that Japanese firms engage in market- and efficiency-seeking foreign direct investment (FDI), and still apply a classic sequence of gradual and incremental market commitments. Market size and growth rate, reducing transaction or transportation costs, and integration within local value chains are the most important to them, whereas competition, creating an export base, lowering tax and accessing skilled labor are of little concern.Practical implicationsThe goal of Japanese FDI in the USA is no longer to bypass tariffs but is still part of a complex industrial network of relations which drives further investment. This result can inform policy makers at the state level about the factors that can drive additional foreign investment, such as the establishment of industrial clusters.Originality/valueThis study offers current insights into the motives of Japanese FDI in two industries.

Edge Intelligence and Blockchain Empowered 5G Beyond for the Industrial Internet of Things

Edge intelligence is a key enabler for IIoT as it offers smart cloud services in close proximity to the production environment with low latency and less cost. The need for ubiquitous communication, computing, and caching resources in 5G beyond will lead to a growing demand to integrate heterogeneous resources into the edge network. Furthermore, distributed edge services can make resource transactions vulnerable to malicious nodes. Ensuring secure edge services under complex industrial networks is a big challenge. In this article, we present an edge intelligence and blockchain empowered IIoT framework, which achieves flexible and secure edge service management. Then we propose a cross-domain sharing inspired edge resource scheduling scheme and design a credit-differentiated edge transaction approval mechanism. Numerical results indicate that the proposed schemes bring significant improvement in both edge service cost and service capacities.

Total site centralised water integration for efficient industrial site water minimisation

Water is used in process industry for a wide range of applications. Water minimisation has received growing attention due to stricter environmental regulations and scarcity of quality water. Rising price of fresh water and cost of wastewater treatment, as well as the relation with the energy (generating emissions) needed for preparing and supplying water, have created an urgent need for efficient water utilisation, especially in the industrial sector. Demand for clean water has been rapidly growing also in the commercial and domestic sector, and very substantially in the agricultural sector. In some regions, water has become a strategic commodity that is even more important than energy. Numerous research works have been performed on Total Site Water Integration (also known as Interplant Water Integration in some papers). However, a superstructure that considers all possibilities of water exchange among sources and demands in industrial sites or a region, are practically challenging to implement since most plants prefer to keep their data and processes confidential. The cost of piping and pumping can be very high due to the need to transfer water across complex industrial water networks. In this study, the option of using centralised headers managed by a third party is explored for a simpler and easy to manage water reuse and recycling among plants. Two centralised water reuse headers with different wastewater quality range, located along a set of plants are proposed. A new Pinch Analysis methodology known as Total Site Centralised Water Integration (TS-CWI) to target the minimum freshwater requirement and wastewater generated resulted from the integration of plants with this centralised water reuse headers are presented. The methodology is illustrated with a case study with 55.1 % of reduction of freshwater requirement and 54.7 % of reduction of wastewater generated.

Analysing an activity in context: A case study of the conditions for vehicle maintenance

The IMP approach is concerned with analysis of complex industrial networks. How to design case studies relying on these theoretical assumptions poses a challenge. In this paper we address this challenge by discussing a case study, focusing on the conditions for maintenance of heavy vehicles. The aim of the paper is to suggest an approach for analysis of embedded activities in industrial networks. The case study takes its starting point in the perspective of an actor considering how to develop vehicle maintenance services for its customers and points at the need to enable understanding of the conditions for vehicle maintenance, which necessitates identification and analysis of the variety across transport service settings.

The co-ordinative practices of temporary organisations

Purpose– This paper aims to explore the necessary mechanisms for coordination in complex industrial networks which are temporary in nature, known as temporary organisations (TOs).Design/methodology/approach– The paper is based on two in-depth case studies conducted in the UK construction industry.Findings– The paper outlines the necessary mechanisms for coordination in TOs – referred to as “scaffolding practices” – which ensure consistency (stability in terms of thinking and action), consensus (agreement) and co-constitutiveness (personal pledges and commitments).Research limitations/implications– The study provides practical implications for situations where actors create temporary organisational specific logics. This “logic” helps explain how actors are able to undertake tasks of finite duration where members lack familiarity and have competing loyalties.Originality/value– The paper is novel in that it represents the first extant attempt to examine “temporary industrial organizations” where individuals from different (often competing) organisations collaborate on a task for a defined period and suggests how coordination may be achieved.

Self-adaptive large-scale SCADA system based on self-organised multi-agent systems

This paper provides an approach for engineering present and future large-scale supervisory control and data acquisition (SCADA) systems as a type of complex industrial networks, which are characterised by their increasing complexity and high distribution. The proposed approach adopts the emerging agent technology, which has proven to be the most representative among artificial systems dealing with complexity and high distribution. Agent-based systems that have the ability to dynamically reorganise themselves will be adaptive enough to survive within their unpredictable and highly changing environments. Adaptive agent-based systems are designed to be capable to adapt themselves to unforeseen situations in an autonomous manner. Engineering modern complex, highly distributed, and large-scale SCADA systems is currently a challenging issue and agents and multi-agent systems (MAS) can provide a feasible solution to this problem. In this paper, a self-adaptive large-scale SCADA system is designed and implemented based on dynamically organised adaptive MAS. A prototype was developed and evaluated within a simulation environment for demonstrating the effect of the transparently realised dynamic reorganisation on the system-to-be performance.

Multiobjective optimization under uncertainty of the economic and life‐cycle environmental performance of industrial processes

The combined use of multiobjective optimization and life‐cycle assessment (LCA) has recently emerged as a useful tool for minimizing the environmental impact of industrial processes. The main limitation of this approach is that it requires large amounts of data that are typically affected by several uncertainty sources. We propose herein a systematic framework to handle these uncertainties that takes advantage of recent advances made in modeling of uncertain LCA data and in optimization under uncertainty. Our strategy is based on a stochastic, multiobjective, and multiscenario mixed‐integer nonlinear programming approach in which the uncertain parameters are described via scenarios. We investigate the use of two stochastic metrics: (1) the environmental impact in the worst case and (2) the environmental downside risk. We demonstrate the capabilities of our approach through its application to a generic complex industrial network in which we consider the uncertainty of some key life‐cycle inventory parameters. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2098–2121, 2014