Are smart manufacturing systems beneficial for all SMEs? Evidence from Korea

PurposeThrough the resource-based view (RBV) and contingency theory, this study empirically investigates the impacts of smart manufacturing systems' maturity levels on the performance of small and medium-sized enterprises (SMEs). Moreover, it aims to examine how industry types (i.e. high- and low-tech industries) and human-resource factors (i.e. the proportion of production workers to total workers) as contingency factors influence the effects of smart manufacturing systems.Design/methodology/approachThe study conducted an empirical investigation of a sample of 163 Korean manufacturing SMEs. This study used an ordinary least squares regression to examine the impacts of the maturity levels of smart manufacturing systems on financial performance. Moreover, the impacts on operational efficiency were analysed using data envelopment analysis based on bootstrap methods and Tobit regression.FindingsThe RBV results indicate that the higher the maturity levels of smart manufacturing systems, the higher the financial performance and operational efficiency. Moreover, based on contingency theory, this study reveals that the effect of the maturity levels of smart manufacturing systems on financial performance and operational efficiency depends on firms' industry types and the proportion of production workers.Research limitations/implicationsThis study shows that the introduction of smart manufacturing systems can help SMEs achieve better financial performance and operational efficiency. However, their effectiveness is contingent on firms' industry types and the characteristics of their human resources.Practical implicationsSince the effects of the maturity levels of smart manufacturing systems on SME performance differ depending on their industries and the characteristics of human resources, managers need to consider them when introducing or investing in smart manufacturing systems.Originality/valueBased on the RBV and contingency theory, this is the first empirical study to examine the moderating effects of industry types and the proportion of production workers on the impacts of the maturity levels of smart manufacturing systems on the financial performance and operational efficiency of SMEs.

A Methodology for Flexible Implementation of Collaborative Robots in Smart Manufacturing Systems

Small-scale production is relying more and more on personalization and flexibility as an innovation key for success in response to market needs such as diversification of consumer preferences and/or greater regulatory pressure. This can be possible thanks to assembly lines dynamically adaptable to new production requirements, easily reconfigurable and reprogrammable to any change in the production line. In such new automated production lines, where traditional automation is not applicable, human and robot collaboration can be established, giving birth to a kind of industrial craftsmanship. The idea at the base of this work is to take advantage of collaborative robotics by using the robots as other generic industrial tools. To overcome the need of complex programming, identified in the literature as one of the main issues preventing cobot diffusion into industrial environments, the paper proposes an approach for simplifying the programming process while still maintaining high flexibility through a pyramidal parametrized approach exploiting cobot collaborative features. An Interactive Refinement Programming procedure is described and validated through a real test case performed as a pilot in the Building Automation department of ABB in Vittuone (Milan, Italy). The key novel ingredients in this approach are a first translation phase, carried out by engineers of production processes who convert the sequence of assembly operations into a preliminary code built as a sequence of robot operations, followed by an on-line correction carried out by non-expert users who can interact with the machine to define the input parameters to make the robotic code runnable. The users in this second step do not need any competence in programming robotic code. Moreover, from an economic point of view, a standardized way of assessing the convenience of the robotic investment is proposed. Both economic and technical results highlight improvements in comparison to the traditional automation approach, demonstrating the possibility to open new further opportunities for collaborative robots when small/medium batch sizes are involved.

Ontology-Based Modelling of State Machines for Production Robots in Smart Manufacturing Systems

The integration of modern IT technologies in production equipment does not only enable them to acquire information from different sources and provide it to others but also to make decisions depending on the situation. Due to the limited processing power of such equipment, usage of state machine to describe and program it is considered a promising direction. However, the necessity of intensive interaction of the equipment units causes problems related to interoperability, which are usually solved with the usage of ontologies. The objective of the presented research is to model state machines of production robots via ontologies. The results are demonstrated on the example of a fragment of an automated production line.

The State of Cybersecurity in Smart Manufacturing Systems: A Systematic Review

With the advent of the so-called 4th Industrial Revolution, personified in the globally commented Industry 4.0, there is a change in progress in manufacturing systems, provided by the development of communication and information technologies, adding an intelligence component in manufacturing plants, through the possibility connectivity and interaction throughout the production chain (intelligent manufacturing systems or cyber-physical systems). However, this new paradigm has an extremely sensitive component, which is the question of the security of the data that is transferred and of the production processes itself. Due to this premise, this article proposed to bring, through a systematic literature review, research about the academic works related to security in these new manufacturing structures (smart manufacturing systems), analyzing which strategies, methodologies, techniques, and technologies have currently used to learn about their vulnerabilities and mitigate possible attacks.

Blockchain for smart manufacturing systems: a survey

Purpose Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas. Design/methodology/approach A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications. Findings The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research. Originality/value This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice.

A GEMMA-GRAFCET Generator for the Automation Software of Smart Manufacturing Systems

Within the Industry 4.0 revolution, manufacturing enterprises are transforming to intelligent enterprises constituted by Smart Manufacturing Systems (SMSs). A key capability of SMSs is the ability to connect and communicate with each other through Industrial Internet of Things technologies, and protocols with standard syntax and semantics. In this context, the GEMMA-GRAFCET Methodology (GG-Methodology) provides a standard approach and vocabulary for the management of the Operational Modes (OMs) of SMSs through the automation software, bringing a common understanding of the exchanged data. Considering the lack of tools to implement the methodology, this work introduces an online tool based on Model-Driven Engineering–GEMMA-GRAFCET Generator (GG-Generator)–to specify and generate PLCopen XML code compliant with the GG-Methodology. The proposed GG-Generator is applied to a case study and validated using Virtual Commissioning and Dynamic Software Testing. Due to the consistency obtained between the GG-Methodology and the generated PLC code, the GG-Generator is expected to support the adoption of the methodology, thus contributing to the interoperability of SMSs through the standardization of the automation software for the management of their OMs.

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited in two aspects: (1) the highly diversified understandings of SM may lead to overlapped, missed, and non-systematic research efforts in advancing the theory and methodologies in the field of SM; (2) few works have been found that focus on the development of generic design methodologies for smart manufacturing systems from the practice perspective. The novelty of this paper consists of two main aspects which are reported in two parts respectively. In the first part, a simplified definition of SM is proposed to unify the existing diversified expectations, and a newly developed concept named digital triad (DT-II) is adopted to define a reference model for SM. The common features of smart manufacturing systems in various applications are identified as functional requirements (FRs) in systems design. To model a system that is capable of reconfiguring itself to adapt to changes, the concept of IoDTT is proposed as a reference model for smart manufacturing systems. In the second part, these two concepts are used to formulate a system design problem, and a generic methodology, based on axiomatic design theory (ADT), is proposed for the design of smart manufacturing systems.