A Framework of a Smart Injection Molding System Based on Real-time Data

“…For this reason, other articles outside the sample of 151 articles and reached by searching on Scopus and WoS the combination of the keywords "cyber-physical system", "manufacturing" with any of the characteristics reported in Tables A. 1 and A.2, contributed to build the results sections (i.e. sections 3 and 4).…”

Section: Figure 2 Researchers With Multiple Authorship Within the Samplementioning

confidence: 99%

“… Modularity. Modularity is the capability of a CPS to be modularized, flexibly changed, and reconfigured in response to rapidly changing customer needs and product changes [1,9,70]. Thus, modularity allows system independence, making it capable to adapt more flexibility [29].…”

Section: Modularity Autonomy Self-capabilities Decentralization (C4)mentioning

confidence: 99%

“…Nowadays, manufacturing firms are facing the challenge of keeping their competitiveness despite a scenario whose protagonists are the unpredictability of market requirements and technological evolution [1][2][3][4]. In this context, fervent research activity is addressing the development of Cyber-Physical Systems (CPSs) in manufacturing: according to literature, CPSs can quickly adapt to unexpected changes [5,6], improving the competitiveness of firms [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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A review on the characteristics of cyber-physical systems for the future smart factories

Napoleone

Macchi

Pozzetti

2020

Journal of Manufacturing Systems

141

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The emergence of new technologies is providing new ways to compete in the current context of changeable and unpredictable market requirements. The focus of this paper is on Cyber-Physical Systems (CPSs), as one of the most promising transformative technological concept of such a context, thus considered by literature as the building blocks of future smart factories. However, CPSs are still in their conceptualization phase. To this end, much literature effort has been put on their technological characterization, while there is a lack of knowledge on operations management characterization to manage such new systems. To contribute in this latter direction, this paper reviews literature in order to distinguish between technological characteristics of CPSs and operations management characteristics to build future CPS-based smart factories. This paper remarks the need for research on operations management characteristics as these may be the ones actually leading operations managers to the concrete implementation of CPS-based factories in manufacturing.

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“…[ 30] 2017 This study proposes a framework for the structural characteristics of a smart factory that can derive the local or global optimal solution for the injection molding system and accumulate know-how, which can be used to anticipate future abnormal symptoms.…”

Section: Prior Approachesmentioning

confidence: 99%

IIoT Framework for SME level Injection Molding Industry in the Context of Industry 4.0

Priyashan

Thilakarathne

2020

Int. j. eng. manag. res.

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The Internet of Things (IoT) is a hype topic for nearly a decade now. Broadly growing, millions of devices get direct access to the Internet provides plenty of applications such as smart homes or mobile health management. This trend can also be found in the industry where IoT components hardened for these environments are introduced, called Industrial IoT (IIoT) devices which can be either sensors or actors, as well as mobile equipment such as smartphones, tablets, and smart glasses. Consequently, mobile communication becomes universal in smart factories. IIoT devices provide massive data on temperature, pressure, machine states, etc. But still, most of the SME level industries in the Asian region are new to these technological advancements. They still operate their facilities ith conventional setups without absorbing the new opportunities which are presented by IoT. In the plastic injection molding industry, process parameters perform a significant role in the quality of the output product. During the manufacturing process, these process parameters have to deal with various factors such as quality and type of materials, requirement tolerance levels of the output product, Environmental conditions like temperature and humidity, etc. Injection molding has been a challenging process for many SME level manufacturers to produce products while meeting the quality requirements at the lowest cost. Most of them are unable to reach the global market in the injection molding industry due to the non-availability of the proper methods to determine the process parameters for injection molding. During production, quality characteristics may differ due to drifting or shifting of processing conditions caused by machine wear, environmental change, or operator fatigue. By determining the optimal process parameter settings productivity and quality will increase while reducing the cost of production. In this paper, we suggest an Industrial IoT framework that can develop for small- and medium-sized enterprises (SMEs) level industries to optimize their production facility. With the presented framework SME level industries can start to inherit IoT devices into their production floor to manage and monitor production parameters in real-time while improving the quality of the production.

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A Framework of a Smart Injection Molding System Based on Real-time Data

Cited by 30 publications

References 11 publications

A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions

A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions

A review on the characteristics of cyber-physical systems for the future smart factories

IIoT Framework for SME level Injection Molding Industry in the Context of Industry 4.0

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