The integration and application of a warehouse system and manufacturing system has become a manufacturing problem for enterprises. The main reason is that the information control system based on automation and stereo warehouse is inconsistent with the production and management information system of the enterprise in terms of business, data, functions, etc. Based on this, this paper studies the implementation of an automated warehouse based on the integration of ERP (enterprise resource planning) and WMS (warehouse management system) with the method and technology of the intermediate table. Moreover, MES (manufacturing execution system) is the brain and the core part of a sustainable digital factory. The enterprise adopts advanced intelligent and information technology to build and deploy the MES, realize fine management and agile production, and meet the personalized needs of the market. Therefore, this paper studies the implementation path and effect based on MES from an industrial realization to construct a sustainable digital factory. The research results of this paper can improve industrial efficiency and reduce costs for enterprises in storage capacity, handling capacity, response rate, rate of error, number of operators, etc.

In any industry, Equipment Asset Management (EAM) is at the core of the production activities. With the rapid development of Industrial Internet technologies and platforms, the EAM based on the Industrial Internet has become an important development trend. Meanwhile, the paradigm of EAM is changing, from a single machine to integrated systems, from the phase of using them to the end of their lifecycle, from breakdown maintenance to predictive maintenance, and from local decision-making to collaborative optimization. However, because of the lack of a unified understanding of the Industrial Internet platforms (IIPs) and the lack of a comprehensive reference architecture and detailed implementation framework, the implementation of EAM projects will face greater risks according to special needs in different industries. Based on the method of system engineering, this study proposes a general reference model and a reference architecture of implementation for the Industrial Internet Solution for Industrial Equipment Asset Management (I3EAM). Further, to help enterprise to evaluate and select their best-fit I3EAM scheme and platform partner, we proposed a set of performance indicators of I3EAM schemes and a quantitative decision-making method based on fuzzy DEMATEL-TOPSIS. Finally, a case study for an I3EAM in automated container terminals was conducted. In the multi-criteria decision environment with complex uncertainty, the project group identified the I3EAM metrics priorities and social digitalization platforms that were more in line with the actual needs of the automated container terminal and firms. The complexity and time of the decision-making process were dramatically reduced. In terms of feasibility and validity, the decision result was positively verified by the feedback from the enterprise implementation. The given model, architecture, and method in this study can create a certain reference value for various industrial enterprises to carry out the analysis and top-level planning of their I3EAM needs and choose the partner for co-implementation. In addition, the research results of this study have the potential to support the construction of standard systems and the planning and optimization of the cross-domain social platform, etc.

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Smart product service ecosystem (SPSE) has multi-level complexity. It is necessary to find a method to describe the hierarchical nested relationship and topological relationship of the structure of SPSE, so as to provide a systematic reference for the construction of industrial SPSE such as smart home and smart Internet-connected vehicle. Moreover, the explanatory ability of ecological service organization is insufficient, and there is a lack of accurate quantitative analysis and modeling tools. Therefore, this paper studies a survival system model and structural modeling for SPSE on sustainability using EVSM (eco-viable system model). In terms of case analysis, this paper applies the proposed methods and technologies to the structural modeling of smart home service ecosystem. The results show that EVSM model can intuitively analyze the nested hierarchical relationship of smart home service ecosystem through graphical method. This set of systematic methods has important application value for guiding the construction of system structure model of similar smart product service ecosystem and analyzing key growth and stability indicators.

Compared with the conventional industrial product–service system, the smart industrial service ecosystem (SISE) mentioned in this study contains more service activity according to the characteristics of the industrial context, participation of various stakeholders and smart interconnected technologies. This study proposes a detailed modularization design framework for SISE, which can be referenced in various industrial contexts. Firstly, the context-based smart industrial service identification blueprint (SISIB) is proposed to describe the operation model of SISE and identify the service components. The SISIB can ensure that the designers understand the service and work process of the system and improve or carry out the smart industrial service (SIS) component identification. In the case of this article, SIS components from different industrial levels can be systematically identified. Secondly, smart collaboration and sustainable development principles are proposed for measuring the correlation degree among the service components. Considering the complexity and multi-level distribution nature of service components, the hyperedge concept is presented to realize the correlation comparison among the service components, and the evaluation linguistics is applied to handle the decision uncertainties. With this method, the effective correlation comparison between service components can be formed with few hyperedges. Thirdly, the hypergraph clustering theory is applied to define the SISE service module partition. The triangular fuzzy number is first used in hyperedge strength evaluation to comply with the vague linguistics from service design experts. The normalized hypergraph cut principle is realized using the K nearest neighbors (kNN) algorithm, and with this method, the new unified hypergraph and related Laplace matrix can be obtained. Then, the relevant eigenvalue of that Laplace matrix is gained, and the component clustering visualization is realized using the k-means algorithm. After the clustering is performed, several modular design schemes can be gained. In order to select the best modularization scheme, we referenced the modularity concept and realized the quality measurement for the modular design using hypergraph modularity criteria. Regarding these three steps, a detailed modularization case study for a renewable electricity service ecosystem design is presented to verify the viability and feasibility of the study in service modular design. The result showed that the framework in this study can realize the visible and clearance service component identification in a smart connected multi-level industrial context. The modular design scheme based on hypergraph can also achieve high modularity with a more convenient correlation evaluation.