A study on performance evaluation and status-based decision for cyber-physical production systems

Chapter 4 - Analysis of factors influencing smart and sustainable manufacturing systems using a multi-criteria decision making tool

When cyber-physical systems (CPS) are connected to perform smart manufacturing, we have a cyber-physical production system (CPPS). In such systems, CPS collaborate in an intelligent way to obtain and maintain the optimum of the manufacturing process, handle disturbances and adapt to changing conditions. This work, based on a systematic literature review, shows current trends in cyber-physical production systems with a special focus on the role of connectivity and control systems in production. We are looking for the enablers of CPPS focusing on the current evolution of control systems in the smart factory of the future. As a result, a conceptual framework as well as a CPPS control system architecture for the introduction and organisation of enablers for CPPS is presented to support practitioners in the realisation of smart manufacturing control concepts.

Denial of Service is a significant availability threat in Industrial Cyber-Physical systems and smart manufacturing is not an exception. The types, methods, and duration of these attacks have been evolving rapidly and their number has increased dramatically, reaching a new record in history. In particular, digitisation of the manufacturing process and increased connectivity have created a battleground between product quality of service and threats associated with cross-domains and multi-vector attacks that affect the manufacturing system performance. The existing research on cyber-threats related to smart manufacturing system does not consider the comprehensive landscape of denial of service attacks. In this study, we classify well-accepted (distributed) denial of service attacks according to a proposed taxonomy, focusing on both the multi-vector attacks and cross-domain attacks. Utilising the taxonomy, more than fifty different denial of service attacks on smart manufacturing system were classified in terms of Endpoint and Network (distributed) denial of service attacks. As an example, a Cyber-Physical Conveyor System was used to examine the proposed taxonomy.

In this paper, the authors proposed a set-theoretic model of the functioning of Smart Manufacturing (SM) system. As part of the work, an analysis of existing scientific works in the subject area was carried out. We focus on the description of the model of SM functioning as a cyber-physical system, as a result of which the physical and informational level of the model functioning are considered. The conditions and tasks for the SM functioning are defined, various types of representation of the information space are considered, and the system of access control to elementary messages is described. As one of the components of digital production, a description of the logistic system was proposed and the main parameters of its functioning were determined.

Industry 4.0, a new industry initiative in Germany, is impacting strongly both on industry and on society. Many newspapers and technical magazines are publishing the state of the art articles on topics such as smart manufacturing based on IoT (Internet of Things), CPPS (Cyber Physical Production System), and cloud-based systems. Other parts of the world have started initiatives such as the IIC (Industrial Internet Consortium) in the US and the IVI (Industrial Value Chain Initiative) in Japan. Smart manufacturing is the key concept underlying these new initiatives. This special issue addresses the most advanced research on smart manufacturing. Subjects cover cyber-physical product-service systems, machinery production lines, manufacturing system simulation, lot-size energy-consumption dependence per production throughput unit, additive manufacturing processes, sensor network technology, production management technology, supply chain management technology, and smart manufacturing reviews. We thank the authors for their careful work and the reviewers for their incisive efforts without which this special issue would not have been possible. We hope that this special issue will trigger further research on smart manufacturing and its advances.

The research proposes a metric referred to as Smart Manufacturing Performance Measures (SMPMs), which are mapped with manufacturing decisions (structural and infrastructural) and manufacturing outputs (cost, quality, delivery, flexibility, and innovativeness). The mapping between manufacturing decisions, manufacturing outputs, and SMPMs, facilitates the organization in choosing SMPMs to deliver desired output as represented by the competitive priority. The approach provides a direction for the practitioners to implement and operate smart manufacturing systems efficiently and effectively by devising a performance measurement system. A total of 22 performance measures are identified through an in-depth literature review. These are further classified into hard and soft measures, which allow decision-makers to measure SMPMs and focus on a specific performance measure. Further, SMPMs is linked to 13 enablers, which are the driving technologies for implementing smart manufacturing systems. Smart manufacturing is evolving, and its implementation is still in the nascent phase. The proposed approach plays a vital role in redefining the manufacturing strategy while deploying smart manufacturing systems. The research contribution is a step-in assessment of smart manufacturing to understand the ‘what’ and ‘how’ of technological changes are transforming the operations and driving outputs.

Cyber-physical production systems are highly flexible systems that enable adaptive production processes. In these systems, all participants of the production process possess individual information about themselves and are equipped with sensors, actors, and communication interfaces. They can interact with each other and autonomously develop and execute process relevant decisions. For each component, a standard process sequence and alternative process sequences are defined. If a deviation in the standard process occurs during the production of an individual component, the process participants can interact with each other and autonomously define an appropriate response strategy and execute it by using actors of the participants and the intralogistics. Regardless of the deviation, the manufacturing and assembly process of individual components in cyber-physical production systems can still proceed. For this purpose, process deviations and the response behavior of cyber-physical production systems are analyzed, modeled, and simulated, to illustrate the benefits of cyber-physical production systems and to develop a process deviation management system for actual, physical production systems based on cyber-physical systems.

Context-aware workflow management for smart manufacturing: A literature review of semantic web-based approaches

The purpose of this paper is to collect and structure the various features of Smart Manufacturing (SM). Researchers have previously identified various characteristics and technologies of Smart Manufacturing System (SMS); this paper collects, discusses and merges some of those characteristics and technologies available in the current body of knowledge. In the future, it is expected that this selection of characteristics and technologies will help to compare and distinguish other initiatives like Industry 4.0, smart factory, intelligent manufacturing, distributive manufacturing, etc. which are frequently used synonymous with SM. The result of this paper is a comprehensive list of characteristics and technologies that are associated with a SMS. As many of the listed items show variating overlaps, certain technologies and characteristics are merged and clustered. This results in a set of five defining characteristics and ten technologies that are considered relevant for a SMS. The authors hope to provide a basis for a broad and interdisciplinary discussion within the SM community about the defining technologies and characteristics of a SMS.

Cyber-Physical Production Systems (CPPS) and Smart Products are considered key features in the development of the fourth industrial revolution. To create a connected environment in manufacturing based on CPPS, components must be able to store and exchange data with machines, and with other components and assemblies along the entire production system. At the same time, Smart Product features require that products and their components be able to store and exchange data throughout their entire lifecycle. Therefore, the aim of this paper is to present a preliminary integrated component data model based on Unified Modeling Language (UML) for the implementation of CPPS and Smart Product features. The development of the data model is based on requirements gathered both from the literature review and from corporate interviews with potential users. The results are still preliminary since the research results are part of a bigger research effort under an international collaboration network.

A problem-solving ontology for human-centered cyber physical production systems

A method for supporting the transformation of an existing production system with its integrated Enterprise Information Systems (EISs) into a Cyber Physical Production System (CPPS)

Cyber-physical systems (CPS) in supply chain management: from foundations to practical implementation

A framework for human-centered production planning and control in smart manufacturing

V-model based development of cyber-physical systems and cyber-physical production systems