Understanding the Digital Transformation Called Industry 4.0

Laird, Karen

doi:10.1002/j.1941-9635.2017.tb01637.x

Cited by 7 publications

(5 citation statements)

References 0 publications

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“…-Customer-centric element: most of the previous definitions totally neglect the voice of the customer when talking about transformation processes. However, listening to the customer is very crucial in formulating the organisation Digital Transformation process to ensure that it will increase customer satisfaction and hence increase profitability (Dombrowski & Fochler, 2018;Horvath et al, 2018;Laird, 2017). -Continuity element: Digital Transformation is a process that never ends.…”

Section: Vial (2019)mentioning

confidence: 99%

“…Another challenge is the resistance of change for existing employees. Current employees used to work on old systems and old structures; they do not want to move from their comfort zones (Kunii & Hasegawa, 2019;Laird, 2017;Rojo Abollado et al, 2017). This resistance requires managing the change process and unfreeze the status quo to make the required modifications.…”

Section: Change Management Processmentioning

confidence: 99%

“…As stated in the proposed definition of Digital Transformation, it is a customer-centric mechanism. Therefore, the organisation implementing Digital Transformation will listen more to the voice of the customer in every aspect (Cozmiuc & Petrisor, 2018;Drake, 2019;Ismagilova et al, 2019;Laird, 2017). This communication occurs from the beginning of designing the product to the manufacturing processes with the right cost to delivery channels convenient to the customer and after-sale services.…”

Section: Benefits Of Implementing Digital Transformationmentioning

confidence: 99%

“…financial sector and government domain). Moreover, there is no sufficient literature review studies had been taken to address this concept in the manufacturing industry (Anwer et al, 2019b;Laird, 2017;Li et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Understanding digital transformation in the manufacturing industry: a systematic literature review and future trends

Abdallah¹,

Shehab²,

Al-Ashaab³

2021

Product

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Digital transformation is one of the most evolving areas both in the research literature and in industrial applications. No doubt that this process will be crucial in the survival of any manufacturing organisation in the future, especially during the current COVID-19 crisis. This paper aims to present a review of the concept in the manufacturing industry through the literature currently available on the topic. The literature was classified, and the results of each study were analysed. From this review, six critical findings have been identified in this paper. First, this paper proposes a definition of Digital Transformation and its concept development in the manufacturing industry. Moreover, significant challenges that exist in the manufacturing industry in the implementation of the digital transformation process have been classified as well as the major enabling technologies that help to implement the Digital Transformation. Finally, the benefits of implementing Digital Transformation in the manufacturing industry and its impact on the manufacturing ecosystem have been highlighted. Following a comprehensive review of the literature, future research directions are formulated to identify abundant research opportunities.

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Section: Vial (2019)mentioning

confidence: 99%

Section: Change Management Processmentioning

confidence: 99%

Section: Benefits Of Implementing Digital Transformationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Understanding digital transformation in the manufacturing industry: a systematic literature review and future trends

Abdallah¹,

Shehab²,

Al-Ashaab³

2021

Product

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“…Industry 4.0 focuses on the ability of "smart" machines to perform autonomously and provide statistical data on their physical processes. The smart machine data is monitored by cyber physical systems (CPS)s, which are equipped to make decisions based upon measured feedback via high-end sensors, microcontroller units and software [5]. Smart machines and factories use advanced technologies such as networking, connected devices, data analytics, and artificial intelligence to reach more efficient Predictive Maintenance (PdM).…”

Section: Introductionmentioning

confidence: 99%

A predictive maintenance cost model for CNC SMEs in the era of industry 4.0

Adu-Amankwa

Attia

Janardhanan

et al. 2019

Int J Adv Manuf Technol

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Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting Predictive Maintenance (PdM) techniques for Machine Tools (MT)s. Authors identified no studies focusing on presenting a PdM value analysis or cost model specifically for Small-Medium Enterprise (SME)s operating Computer Numerically Controlled (CNC) MTs. This paper's novelty is addressing SMEs minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804-£48,585 over a range of 1-50 CNC MTs maintained on a Distributed Numerically Controlled (DNC) network. Affirms PdM's tangible value creation for SME CNC machine shops with predicted positive impacts on their MTs cost and performance drivers. These exploratory research findings corroborates SMEs pooling together to optimize their CNC MT maintenance cost through the recommended system architecture. Finally, introduces opportunities for further PdM research taking into account SMEs' perspective. The paper's industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT's overall life cycle costs.

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