scholarly journals On Architecting and Composing Engineering Information Services to Enable Smart Manufacturing

2016 ◽  
Vol 16 (3) ◽  
Author(s):  
Boonserm (Serm) Kulvatunyou ◽  
Nenad Ivezic ◽  
Vijay Srinivasan
Keyword(s):  
Information Systems ◽  
Research And Development ◽  
Manufacturing Systems ◽  
Information Services ◽  
Smart Manufacturing ◽  
Engineering Information ◽  
Smart Manufacturing Systems

Engineering information systems play an important role in the current era of digitization of manufacturing, which is a key component to enable smart manufacturing. Traditionally, these engineering information systems spanned the lifecycle of a product by providing interoperability of software subsystems through a combination of open and proprietary exchange of data. But research and development efforts are underway to replace this paradigm with engineering information services that can be composed dynamically to meet changing needs in the operation of smart manufacturing systems. This paper describes the opportunities and challenges in architecting such engineering information services and composing them to enable smarter manufacturing.

An integrated framework of enterprise information systems in smart manufacturing system via business process reengineering

2018 ◽  
Vol 233 (11) ◽  
pp. 2210-2224 ◽  
Author(s):  
Yuanju Qu ◽  
Xinguo Ming ◽  
Yanrong Ni ◽  
Xiuzhen Li ◽  
Zhiwen Liu ◽  
...  
Keyword(s):  
Information Systems ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Process Reengineering ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Traditional Manufacturing ◽  
Systems Framework ◽  
Smart Manufacturing Systems

Enterprise information systems play a significant role in the Industry 4.0 era and are the crucial component to realize smart manufacturing systems. However, traditional enterprise information systems have some limits: (1) lack of complete information, (2) only satisfy limited business needs, and (3) lack of seamless integration, business intelligence, value-driven processes, and dynamic optimization. Clearly, the existing enterprise information systems are unable to satisfy the requirements for smart manufacturing systems: (1) autonomous operation, (2) sustainable values, and (3) self-optimization. In addition, smart manufacturing systems have become more efficient and effective, demanding for seamless information flow in enterprise information systems, knowledge, and data-driven accurately decision. Therefore, a new enterprise information systems framework is needed to bridge gaps between the requirements for traditional manufacturing system and smart manufacturing system. In this article, the integrative framework is proposed based on the business process reengineering, lean thinking, and intelligent management methods, with inclusion of six enterprise information systems aspects to provide upgrading guidelines from traditional manufacturing to smart manufacturing. The procedure of this method contains three steps: (1) it identifies requirements and acquires best practices using AS-IS model, (2) it redesigns six aspects of enterprise information systems using TO-BE model, and (3) it proposes a new enterprise information systems framework. Finally, the proposed framework is validated by real cases.

scholarly journals A Model for Working Environment Monitoring in Smart Manufacturing

2021 ◽  
Vol 11 (6) ◽  
pp. 2850
Author(s):  
Dalibor Dobrilovic ◽  
Vladimir Brtka ◽  
Zeljko Stojanov ◽  
Gordana Jotanovic ◽  
Dragan Perakovic ◽  
...  
Keyword(s):  
Open Source ◽  
Student Teaching ◽  
Manufacturing Systems ◽  
Working Environment ◽  
Smart Manufacturing ◽  
Environment Monitoring ◽  
Application Development ◽  
Testing Platform ◽  
Proposed Model ◽  
Smart Manufacturing Systems

The growing application of smart manufacturing systems and the expansion of the Industry 4.0 model have created a need for new teaching platforms for education, rapid application development, and testing. This research addresses this need with a proposal for a model of working environment monitoring in smart manufacturing, based on emerging wireless sensor technologies and the message queuing telemetry transport (MQTT) protocol. In accordance with the proposed model, a testing platform was developed. The testing platform was built on open-source hardware and software components. The testing platform was used for the validation of the model within the presented experimental environment. The results showed that the proposed model could be developed by mainly using open-source components, which can then be used to simulate different scenarios, applications, and target systems. Furthermore, the presented stable and functional platform proved to be applicable in the process of rapid prototyping, and software development for the targeted systems, as well as for student teaching as part of the engineering education process.

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

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Soojeen Jang ◽  
Yanghon Chung ◽  
Hosung Son
Keyword(s):  
Human Resources ◽  
Financial Performance ◽  
Manufacturing Systems ◽  
Contingency Theory ◽  
Ordinary Least Squares ◽  
Operational Efficiency ◽  
Smart Manufacturing ◽  
Least Squares Regression ◽  
Content Type ◽  
Smart Manufacturing Systems

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.

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