Real-Time Process Monitoring in Industry 4.0 Manufacturing Systems: Sensing, Smart, and Sustainable Technologies.
In the framework of Industry 4.0, Internet of Things and cyber-physical system technologies bring forward cognitive automation to carry out intelligent manufacturing, thus catalyzing smart products and services. (Kunst et al., 2019) Industry 4.0 can qualitatively improve factory work, bringing about a more dynamic labor setting, superior self-governance and prospects for selfdevelopment. (Kaasinen et al., 2019) Industry 4.0 technologies can offer increased adjustability and may enhance the quality of the commodities due to superior monitoring of the production process. (Dachs et al., 2019)
2. Conceptual Framework and Literature Review
Organizations should refashion their operational structure to constitute a viable establishment for Industry 4.0. (Veile et al., 2019) The volume of energy demand has boosted because of the machine control of the manufacturing and industrial plants to conform them to Industry 4.0 requirements. (Shukla et al., 2020) Innovation can take place as a component of a high-tech networked sector and because of the tendency of firms to get up to date to a greater extent in Industry 4.0. (Buchi et al., 2020) Machine learning entails that a cutting-edge system or a smart algorithm is assimilating knowledge without being thoroughly programmed and inherently can bring to light models that facilitate prediction. (Hofmann et al., 2019) Industry 4.0 may diminish the required labor input and consequently reposition the balance between capital and labor inputs in preference to the former. (Dachs et al., 2019)
3. Methodology and Empirical Analysis
Building our argument by drawing on data collected from Accenture, BBC, BDO, Capgemini, McKinsey, and PwC, we performed analyses and made estimates regarding progress in the last year in implementing Industry 4.0 applications/strategies (%), digital intensity parameters (%), data monetization strategies (%), and current level of process integration (%). Data collected from 4,700 respondents are tested against the research model by using structural equation modeling.
4. Results and Discussion
Industry 4.0 technologies may beneficially impact the lifecycle management of commodities. (Rosa et al., 2019) Horizontal chains of command, adjustable structures and operations, and decentralized environments can constitute an agile company in conformity with Industry 4.0 standards. (Veile et al., 2019) A pivotal component of Industry 4.0 is human-centricity. (Kaasinen et al., 2019) Decreasing the servicing, infrastructure, and reorganization expenses, while furthering the adjustability are standard objectives for networking systems in Industry 4.0 (Zeng et al., 2019) (Tables 1-7)
5. Conclusions and Implications
In Industry 4.0, the technological developments are enabling competitive value creation in all advancements phases (Andrei et al, 2016; Balica, 2018; Neary et al., 2018; Popescu Ljungholm, 2018; Popescu et al., 2019), via cost-effective design, resource-efficient manufacturing operations, and repetitive and synergetic production systems. (Machado et al, 2019) Networking taking place in the physical realm may transform the processing performance in the virtual one, in a determining link that can be harnessed for the permanent enhancement of operations. (Delicato et al, 2019) Industry 4.0 attempts to assimilate production processes into a coherent digital unit (Androniceanu and Popescu, 2017; Lazaroiu, 2018; Nica et al, 2014; Popescu et al, 2018; Valaskova et al, 2018) by integrating adjustability, agility, reorganization, and soundness. (Barenji et al, 2019)
The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States. The precision of the online polls was measured using a Bayesian credibility interval.
This paper was supported by the Slovak Research and Development Agency under Grant no. APW-17-0546: Variant Comprehensive Model of Earnings Management in Conditions of The Slovak Republic as an Essential Instrument of Market Uncertainty Reduction.
All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The Internet-enabled Collective Intelligence Laboratory
at ISBDA, Glasgow, Scotland
email@example.com Faculty of Operation and Economics of Transport and Communications, Department of Economics, University of Zilina, Zilina, Slovak Republic
The School of Expertness and Valuation, The Institute of Technology and Business in Ceske Budejovice, Czech Republic
Natalia A. Zhuravleva
Faculty of Economics and Management, Department of Transport Economics, Emperor Alexander I St. Petersburg State Transport University, St. Petersburg, Russia
Received 6 August 2019 * Received in revised form 10 December 2019
Accepted 12 December 2019 * Available online 15 December 2019
Table 1 Progress in the last year in implementing Industry 4.0 applications/strategies aimed at... (%) Good/substantial No or only progress or implementation limited almost complete progress Suppliers... improving 47 53 operational effectiveness Suppliers... exploring 54 46 new business models Manufacturers... improving 48 52 operational effectiveness Manufacturers... exploring 38 62 new business models Sources: McKinsey; our survey among 4,700 individuals conducted June 2019. Table 2 Digital intensity parameters (%) Majority of processes digitized Digital Masters with Beginners with more than 50% more than 50% processes digitized processes digitized Performance management 92 36 Maintenance management 89 33 Production 86 32 Inventory management 83 31 Quality management 80 35 High leverage of technologies in operations Digital Masters Beginners highly highly leveraging leveraging the the technology technology Big data 89 23 Mobility and 86 26 augmented reality Industrial Internet of Things 78 28 Advanced robotics 60 24 Sources: Capgemini; our survey among 4,700 individuals conducted June 2019. Table 3 How artificial intelligence could change the job market: Estimated net job creation by industry sector (%, 2017-2037) Health +19 Scientific and technical +16 Communications +8 Hospitality +6 Education +5 Administrative and support services -4 Other sectors -7 Wholesale and retail -8 Construction -8 Financial and insurance -10 Public administration and defense -14 Transportation and storage -24 Manufacturing -30 Sources: PwC; BBC; our 2018 estimates. Table 4 Top five prioritized Industry 4.0 applications (%) Technology suppliers Manufacturers Smart energy consumption 23 Real-time supply 24 chain optimization Predictive maintenance 22 Digital quality management 23 Digital quality management 19 Predictive maintenance 20 Remote monitoring and control 18 Digital performance management 19 Real-time supply 18 Remote monitoring 14 chain optimization and control Sources: McKinsey; our survey among 4,700 individuals conducted June 2019. Table 5 How much of a priority is digital manufacturing on your company's direction agenda? (%) Top priority Average or low priority Brazil 76 24 China 91 9 France 62 38 Germany 74 26 India 92 8 Japan 36 64 USA 69 31 Sources: McKinsey; our survey among 4,700 individuals conducted June 2019. Table 6 Data monetization strategies (%) Risk mitigation and fraud detection 74 Customer targeting 69 Free value-add services 66 Product or service customization 68 Data syndication to customers 64 Sources: BDO; our survey among 4,700 individuals conducted June 2019. Table 7 Current level of process integration (%) End-to-end process integration with outside suppliers 4 Functional silos 6 Some process integration with outside suppliers 12 Some process integration 34 End-to-end process integration within the organization 44 Sources: BDO; our survey among 4,700 individuals conducted June 2019.