Data sharing & knowledge graph
Data sharing in Industry 4.0 - AutomationML, B2MML and International Data Spaces-based solutions
The concept of a data ecosystem and Industry 4.0 requires high-level vertical and horizontal interconnectivity across the entire value chain. Its successful realization demands standardized data models to ensure transparent, secure and widely integrable data sharing within and between enterprises. This paper provides a PRISMA method-based systematic review about data sharing in Industry 4.0 via AutomationML, B2MML and International Data Spaces-based solutions. The interconnection of these data models and the ISA-95 standard is emphasized. This review describes the major application areas of these standards and their extension as well as supporting technologies and their contribution towards horizontal integration and data ecosystems. This review highlights how much value interconnected, exchanged and shared data gained in recent years. Standardized data sharing mechanisms enable real-time, flexible and transparent communication, which features became top requirements to gain a competitive advantage. However, to foster the shift from within company data communication towards the data ecosystem, IT- and people-oriented cultures must be well-established to ensure data protection and digital trust. We believe that this review of these standardized data exchange and sharing solutions can contribute to the development and design of Industry 4.0-related systems as well as support related scientific research.
Post date: 03 March 2023
Hypergraph-based analysis and design of intelligent collaborative manufacturing space
A method for hypergraph-based analysis and the design of manufacturing systems has been developed. The reason for its development is the need to integrate the human workforce into Industry 4.0 solutions. The proposed intelligent collaborative manufacturing space enhances collaboration between the operators as well as provides them with valuable information about their performance and the state of the production system. The design of these Operator 4.0 solutions requires a problem-specific description of manufacturing systems, the skills, and states of the operators, as well as of the sensors placed in the intelligent space for the simultaneous monitoring of the cooperative work. The design of this intelligent collaborative manufacturing space requires the systematic analysis of the critical sets of interacting elements. The proposal is that hypergraphs can efficiently represent these sets, moreover, studying the centrality and modularity of the resultant hypergraphs can support the formation of collaboration and interaction schemes and the formation of manufacturing cells. A fully reproducible illustrative example presents the applicability of this concept.
Post date: 06 September 2022
Ontology-Based Analysis of Manufacturing Processes: Lessons Learned from the Case Study of Wire Harness Production
Effective information management is critical for the development of manufacturing processes. This paper aims to provide an overview of ontologies that can be utilized in building Industry 4.0 applications. The main contributions of the work are that it highlights ontologies that are suitable for manufacturing management and recommends the multilayer-network-based interpretation and analysis of ontology-based databases. This article not only serves as a reference for engineers and researchers on ontologies but also presents a reproducible industrial case study that describes the ontology-based model of a wire harness assembly manufacturing process.
Post date: 19 November 2021
Analytic Hierarchy Process and Multilayer Network-Based Method for Assembly Line Balancing
Assembly line balancing improves the efficiency of production systems by the optimal assignment of tasks to operators. The optimisation of this assignment requires models that provide information about the activity times, constraints and costs of the assignments. A multilayer network-based representation of the assembly line-balancing problem is proposed, in which the layers of the network represent the skills of the operators, the tools required for their activities and the precedence constraints of their activities. The activity–operator network layer is designed by a multi-objective optimisation algorithm in which the training and equipment costs as well as the precedence of the activities are also taken into account. As these costs are difficult to evaluate, the analytic hierarchy process (AHP) technique is used to quantify the importance of the criteria. The optimisation problem is solved by a multi-level simulated annealing algorithm (SA) that efficiently handles the precedence constraints. The efficiency of the method is demonstrated by a case study from wire harness manufacturing.
Post date: 05 June 2020
