Six-Gear Roadmap towards the Smart Factory
2. Conceptual Modeling Methodology
3. Review of Similar Concepts and Models
3.1. Academic Contributions
3.2. Industial Contributions
4. Technology Jigsaw Map
5. The Six-Gear Roadmap
5.1. Gear 1: Strategy
5.2. Gear 2: Connectivity
5.2.1. IT/Network Infrastructure
5.2.2. Industrial Internet of Things (IIoT) Connectivity
5.2.3. Cybersecurity Strategy
5.3. Gear 3: Integration
5.4. Gear 4: Analytics
5.5. Gear 5: AI (Artificial Intelligence)
5.6. Gear 6: Scale
5.6.1. Scaling the Roadmap Gears
5.6.2. Other Advanced Technologies for Smart Manufacturing
6. Other Challenges of Digital Transformation for Manufacturing SMEs
6.2. Managing Change
Conflicts of Interest
|Reference||Type||General Features||Industry 4.0 Technology Trends|
|||Technology review||Industry 4.0 technologies and trends relevant to the developments of smart manufacturing.||IoT, BD, CPS, ML, AD, R|
|||Technology review||Characteristics: Context awareness, modularity, heterogeneity, interoperability, compositionality.||IC, IoT, CC, AD, ES, CS, SP, DA, PM, CPS, VT|
|Enabling factors: law and regulations, innovation education and training, data sharing systems.|
|||Technology review, issues, challenges, and conceptual framework of interoperability||5 principles: Accessibility, Multilingualism, Security, Open-source, Multilateral||CC, BD, IoT, MC, CPS, ICT|
|3 applications: Smart Factory/Manufacturing, Smart City, Smart Products.|
|4 architecture levels: Operational, Systematical, Technical, Semantic.|
|||Technology review of internet connected devices in manufacturing||Impact and value of Industry 4.0 and internet connected technologies that enable||IoT|
|new products, services and business models.|
|||Technology review of Industry 4.0 developments and practices for sustainable manufacturing||Conceptual perspective of Industry 4.0 integration.||CPS|
|Micro and Macro integration perspective: Horizontal, Vertical, and End-to-end integration within the smart factory and across the entire product life cycle and value chain.|
|Micro and Macro opportunities for sustainable manufacturing.|
|||Conceptual model for implementing Industry 4.0 technologies in smart manufacturing||3 stage implementations: Vertical Integration, Advanced Automation, Flexibilization.||IoT, CC, BD, DA|
|2 technology layers:|
|Front- end Technology: Smart Manufacturing, Smart Products, Smart Supply Chain, Smart Working.|
|Base- end Technology: IoT, Cloud, BD Analytics.|
|||Conceptual model for implementing CPS’s for manufacturing applications||5 level architecture (5C): Smart Connection, Conversion and Cyber, Cognition and Configure.||CPS, DA|
|||Technology review and conceptual roadmap for digitalisation of the manufacturing industry||6 management principles: Strategy, Marketing, Human Resources, IT Resources, Manufacturing Technology and Supply Chain.||IoT, CC, BD, B, CS, AR, R, AD, CPS, VT|
|12 design principles.|
|14 technology trends.|
|||Literature review, framework architecture for smart manufacturing technologies||4-layer architecture: sensory, integration, intelligent and response||IoT, BD, IC, CPS, MES,|
|||Industrial technology report (BCG)||9 technology pillars for transforming industrial production.||IoT, R, BD, CS, VT, HVI, CC, AD|
|||Industrial technology review report (Automation Alley)||Emerging technology trends, implications, action plans, case studies.||IoT, R, BD, CS, AI, AD, VT, CC|
|||Industrial report on smart factory transition (Deloitte)||5 Features of smart factory.||CS, IoT, AI, AD, AR, R, DA|
|5 Benefits of a smart factory.|
|6 Impact on manufacturing processes.|
|5 Areas of consideration.|
|4 Practical steps towards the smart factory.|
|||Industrial Research, Digital Transformation Framework (LNS Research)||History and future potential of manufacturing systems technologies.||BD, HVI, CC, DA, AI, ML,|
|5 layers: Strategic objectives, Operational excellence, Operational architecture, Business case development, Solution selection.|
|4 recommended actions for digital transformation and smart manufacturing.|
|||Industrial Research, Operational Architecture Framework on applying data analytics. (LNS Research)||Operational architecture framework that focuses on applying data and analytics within the Digital Transformation Framework||BD, AI, CC, IoT|
|4 layers: Industrial operations, Compute and storage, Big data model, Industrial Analytics and Apps|
|||Industrial white paper (Festo)||10 practical tips guide for implementing an Industry 4.0 project.||-|
|||Industrial white paper (ABI research)||5-steps guide to master a digital transition journey.||IoT, R, AR, PLM|
|4 challenges in digital transformation and|
|4 Industry 4.0 technologies that make human the central beneficiaries.|
|||Industrial white paper (Bosch-Rexroth)||3 steps approach for implementing connectivity aspects of Industry 4.0.||IoT|
|||Knowledge base hub white paper (Sensor City)||5-part guide that addresses challenges and presents advice on IoT Adoption.||IoT|
|Case studies on how manufacturers can work towards successful IoT adoption.|
|||Industrial white paper (Six Degrees)||5 steps approach to lay stable IT foundations for the transition to Industry 4.0 ready cloud environment.||IoT, BD, AI, DT, AR, R|
|||Industrial white paper Maturity index for digital transformation (Acatech)||6 Maturity stages: Computerization, Connectivity, Visibility, Transparency, Predictive capacity, Adaptability.||BD, ML, HVI, CPS|
|4 Structural areas: Resources, information systems, Culture, Organizational Structure.|
|5 Functional areas: Production, Logistics, Services, Marketing, Sales.|
|||ATI framework for digital transformation||4 steps: Address digital capability, Leverage digital ecosystem, Stretch collaboration, Create space and safety.||IoT, AR, VR,|
|Platform Name||Company||General Features|
|ThingWorx||PTC||IIoT-C, DA, AI, MOM, AR, DT|
|MindSpher||Siemens||IIoT-C, DA, AI, MOM, CB, DT|
|Tulip Manufacturing Apps||Tulip||IIoT-C, DA, MOM, CB|
|Watson IoT||IBM||IIoT-C, DA, AI|
|Nexceed (PPM)||BOSCH||IIoT-C, DA|
|WISE-PasS||Advantech||IIoT-C, DA, AI, CB|
|Cumulocity IoT||Software AG||IIoT-C, DA, CB|
|AWS IoT||Amazon Web Services||IIoT-C, DA, AI, CB|
|Predix||GE Digital||IIoT-C, DA, AI, CB, DT|
|Azure IoT||Microsoft||IIoT-C, DA, AI, CB|
|SMas||Datahone||IIoT-C, DA, MOM, MES, CB|
|FactoryWiz||FactoryWiz||IIoT-C, DA, MOM, MES|
|machinemetrics||MachineMetrics||IIoT-C, DA, MOM, MES, AI, CB|
|ForcamForce||FORCAM||IIoT-C, DA, MOM|
|keyprod||Keyprod||IIoT-C, DA, MOM, MES|
|Smooth Monitor AX||Yamazaki Mazak||IIoT-C, DA|
|Panorama E2||CODRA||IIoT-C, DA|
|Lumada||Hitachi||IIoT-C, DA, AI, CB|
|KepServer||PTC||IIoT-C, Software Bridge|
|OPCrouter||Inray industrie software||IIoT-C, Software Bridge|
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Sufian, A.T.; Abdullah, B.M.; Ateeq, M.; Wah, R.; Clements, D. Six-Gear Roadmap towards the Smart Factory. Appl. Sci. 2021, 11, 3568. https://doi.org/10.3390/app11083568
Sufian AT, Abdullah BM, Ateeq M, Wah R, Clements D. Six-Gear Roadmap towards the Smart Factory. Applied Sciences. 2021; 11(8):3568. https://doi.org/10.3390/app11083568Chicago/Turabian Style
Sufian, Amr T., Badr M. Abdullah, Muhammad Ateeq, Roderick Wah, and David Clements. 2021. "Six-Gear Roadmap towards the Smart Factory" Applied Sciences 11, no. 8: 3568. https://doi.org/10.3390/app11083568