Complex Manufacturing Network Research Articles

Business-driven digitisation of external manufacturing supply chains

In an increasingly complex world of manufacturing where core internal manufacturing and strategic external manufacturing are tightly intertwined on product roadmaps, it is imperative to have a vision around transforming supply network collaboration to be digitised, core transactional systems automated to achieve reliable, fast decision making at all levels. Increasing product complexity with the need to optimise capacity and cost results in a much more complex manufacturing network as compared to the past. Intel business strategy of IDM 2.0 (Integrated Device Manufacturer) is utilising both internal and external manufacturing to optimally serve the surging global demand of semiconductors. In this paper we show how digitisation and automation drive solutions to the challenges which today’s and expected future semiconductor market poses to the external manufacturing supply chain.

Entropy of complex manufacturing networks as a metric of flexibility

With the advent of Industry 4.0, manufacturing networks are increasingly flexible. However, a means to measure the potential level of flexibility as well as the practically attained one is missing. In this work, production lines are abstracted as directed complex networks and are evaluated using path-transfer flow entropy. Firstly, the path probability distribution of the binary representation of the manufacturing network is used to determine the level of flexibility that a production network can potentially achieve. Then, the weighted representation is employed to illustrate the degree of flexibility displayed in practice. A case study demonstrates the use of this technique and highlights practical limitations.

A framework for credit-driven smart manufacturing service configuration based on complex networks

ABSTRACT Complex cooperative relationships between manufacturing equipment and services make such manufacturing networks have necessary research significance in network science. Under the prevailing background of mass customizing, the continuous coordination between manufacturing services (MSs) in the cloud platform is pulling the complex cooperative relationship between equipment and even enterprises, which constitutes a complex manufacturing network (CMN) from a macro perspective. In this paper, a credit-driven service configuration method is proposed, which is tactfully modeled on the reputation system of Uber. Under such circumstances, MSs could be evaluated combining theirexecution states and historical manufacturing behaviors and chosen as the most appropriate service under the current processing condition to tackle the manufacturing tasks according to customers’ requests accurately. Results in the proof-of-concept simulation show that credit is well integrated with the manufacturing process, and could be utilized to drive the CMN with a four-tier networked architecture on the whole, in which it is taken as the benchmark for the service-and-task smart matching in cases where customer requirements and manufacturing process stability are paramount. Credit also effectively assists MSs in exception self-organization and restrains the diffusion of the influence range of the deterioration of service credit when faced with service failures.

Blockchain architecture for automotive traceability

The automotive value chain comprises a complex manufacturing network, which encompasses several departments, companies, and even countries. In the age of electrification and autonomous driving, the quality and transparency requirements are rising, in particular for electric and electronic components, which contribute to safety-critical functionalities. In this research, we analyze the traceability requirements and liability implications for the automotive manufacturing network. A key component in preventing safety and quality deficiencies in manufacturing processes is a state-of-the-art traceability system. Accordingly, we propose a blockchain-based traceability architecture to achieve the aspired level of transparency and process security. The proposed blockchain architecture processes manufacturing data entries and defines blockchain nodes, access, as well as consensus algorithm and transaction logic. An Ethereum-based blockchain demonstrator validates the architecture by implementing the logic for automotive product configuration and process sequencing based on the semi-fungible ERC 1155 token, the proof of authority consensus, and an automotive product token smart contract.

A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things

Most scheduling problems are required to follow rigid metrics, such as the maximum completion time, earliest deadline first, etc., ignoring the flexibility of manufacturing services (MSs) and the effects of their historical data hidden in millions of manufacturing activities. The historical data serves as a powerful basis for describing the comprehensiveness or credibility of the MS itself with the help of Industrial IoT enabling all equipment to communicate and take preventive actions. Similar to the bank credit for individuals, MSs should also have their own referential credit values when choosing the most suitable service for a specific manufacturing task. This paper summarizes the MS attributes from six aspects with sufficient sub-attributes. The fuzzy Analytic Network Process combined with the Cross-Entropy method is employed to evaluate the credit of MSs in the complex manufacturing network system. Such service scoring mechanism (SSM) can personify a comprehensive credit evaluation of services, where, a smart service configuration mode based on credit is proposed for carrying out the supply–demand matching with the help of the data-security technology. Subsequently, a credit-based manufacturing mode is derived under SSM. Numerical examples are carried out to demonstrate the validity of the matching mode. The result may assist manufacturers to allocate their manufacturing tasks in real time in a “credit” way and make quicker decisions in exceptional circumstances, while making the chosen service truly competent enough to finish the work, so as to further improve the customer satisfaction.

A Heuristic Algorithm for Optimal Service Composition in Complex Manufacturing Networks

Service composition in a Cloud Manufacturing environment involves the adaptive and optimal assembly of manufacturing services to achieve quick responses to varied manufacturing needs. It is challenged by the inherent heterogeneity and complexity of these services in terms of their diverse and complex functions, qualities of service, execution paths, etc. In this paper, a manufacturing network is constructed to explicitly identify and describe the relationships between individual services based on their attributes. On this basis, the service composition problem can be modeled as a multiple‐constrained optimal path (MCOP) selection problem by taking into account different types of composition, namely, sequence, parallel, selection, and cycle. A novel Dual Heuristic Functions based Optimal Service Composition Path algorithm (DHA_OSCP) is proposed to solve the NP‐Complete MCOP problem, which involves exploiting the backward search procedure with different search targets to obtain two heuristic functions for the forward search procedure. The proposed algorithm is evaluated through a set of computational experiments in which the proposed algorithm and other popular algorithms such as MFPB_HOSTP are applied to the same dataset, and the results obtained show that DHA_OSCP can efficiently find the optimal service composition path with better Quality of Service (QoS). The viability of DHA_OSCP is further proved in a case study of services composition on a Cloud Manufacturing platform.

Towards Design for Cyber-Physical Inspection

The ongoing technological advances in information and communication technology have a significant impact on the field of product creation. Their implementation in manufacturing equipment yields cyber-physical production systems, which promise significant increase in flexibility and efficiency concerning value chains and complex manufacturing networks. To ensure the high quality of the designed and manufactured products new ways of inspection is required. This work discusses the use of computer-aided models and tools to realize a cyber-physical inspection. Therefore, a two-staged methodology was applied. At first a brief overview over basic overall approaches and current work in the field of inspection processes as well as promising advances in the field of design and information exchange are presented. The second step analyses the Siemens PLM NX 12 software and correlates the provided functionality with the necessary activities defined in the first phase. Following, the paper discusses arising challenges and necessary extensions to move towards a cyber-physical inspection. Finally a brief conclusion as well as a description of future work is given.

Maximum Flow of Complex Manufacturing Networks

With the advent of Industry 4.0, manufacturing lines have evolved from processing goods in a serial manner to doing so by means of cellular manufacturing. Furthermore, the use of ubiquitous radio-frequency identification tags and cyber-physical systems allow to seamlessly follow goods through the manufacturing plant. The data collected from these can easily be used to abstract manufacturing networks as a directed graph with workstations as nodes and material flows as edges. It is also possible to analyze manufacturing networks in the sense of "flow networks" in order to answer questions about material flows. In a flow network, materials with different levels of processing move through the system from a source (the raw materials storage room, for example) to a sink (like a warehouse for finished goods). Raw materials leave the source at some steady rate, and finished goods arrive to the sink at the same rate. Directed edges act as conduits for material with a stated capacity and vertices (workstations) act as junctions where material flows without accumulating. The present work aims at solving the following optimization problem: given a manufacturing flow network of known edge capacities, determine the theoretical maximum production rate that the network can attain under the assumptions of steady state flow and zero intermediate inventory levels. To accomplish this, the manufacturing network must be analyzed in terms of complex networks and graph theory and the results subsequently interpreted in terms of Operations Research. Finally, the method is illustrated with the analysis of the manufacturing network of an appliances manufacturer by determining the maximum theoretical production rate and the network bottleneck.

Dynamic scheduling in RFID-driven discrete manufacturing system by using multi-layer network metrics as heuristic information

Since discrete manufacturing system (DMS) is a complicated dynamic network that comprises of processes, machines, and work in process, a coherent methodology for performance tracking and sustainable improvement at the system/network level is of great significance for manufacturers to respond rapidly in a mass customization paradigm. Fortunately, the radio frequency identification (RFID) technologies provide us the real-time tracking ability of the production process that suffers unpredictable and recessive disturbances. This paper proposes a dynamic scheduling approach based on multi-layer network metrics of RFID-driven DMS. Firstly, considering the elements of DMS (e.g., parts, manufacturing activities, and equipment) and relationships among them, a DMS model named complex manufacturing network (CMN) is proposed. Then, several multi-layer network metrics of the CMN are defined and analysed. The implications of these metrics lead to a better understanding of the current status and performance of DMS. Thirdly, a dynamic scheduling algorithm using these metrics as heuristic information is proposed to solve multi-resources and independent-task DMS. Finally, a Printing Machine manufacturing system is chosen as an example to illustrate the feasibility of the proposed approach.

Simulation-Based Evaluation of Quality Control Strategies in Global Manufacturing Networks

In the context of an increased globalisation of sales and procurement markets companies are distributing their manufacturing activities in global networks. A key challenge is to ensure the overall production quality despite distributed value creation processes in complex manufacturing networks. Hence, a simulation model is presented, which allows for an evaluation of quality control strategies in global manufacturing networks. Based on the approach of Value Stream Mapping (VSM), which is enhanced by quality-relevant elements, a simulation approach is developed to dynamically evaluate different quality control strategies taking the individual target systems and site roles of the involved partners in the manufacturing network into account.

Priority-Based Distributed Manufacturing Process Modeling via Hierarchical Timed Color Petri Net

Petri net (PN) is a classical tool for modeling, simulation, and analysis. With the emergence of distributed manufacturing system (DMS), PN has been evolved into different forms such as colored PN (CPN) and timed PN (TPN). To fulfill the practical requirements, CPN has been extended to a larger and more complex model. Meanwhile, DMS becomes an important issue for industry, and how to model a complex manufacturing network for better throughput needs further investigation. A simple single type of PN only cannot fulfill all contemporary requirements at the same time. This paper proposes a new concept for a new PN-hierarchical timed CPN (HTCPN), which can be a powerful tool for modeling, simulation, and analysis for current large complex distributed manufacturing system. This paper presents a general structure of DMS and uses HTCPN to model the manufacturing system as discrete event with dynamic behavior. The proposed approach shows superiority on modeling large complex manufacturing system as it represents the material flow and transitions clearly and provides overview and detailed description for DMS.

Research on Quality Control Processes Management in Manufacturing Network Based on Workflow and Multi-Agent

In this paper, The author researched the integrated management of quality control processes in manufacturing network using workflow and multi-agent technologies, analyzed the advantages and basic ways of integrated application of these two technologies, established Quality Control Processes Workflow Managed by Agents (QCPWMA) model and discussed the agents’ structure, configuration and execution and so on, then using this model to realize integrated and collaborated management of dispersed quality control processes workflow in manufacturing network. Through this research it can further improve enterprise's ability of quality processes control in complex manufacturing network environment.