Smart manufacturing

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Smart manufacturing [1] is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. [2] Other goals sometimes include fast changes in production levels based on demand, [3] [1] optimization of the supply chain, [3] efficient production and recyclability. [4] In this concept, as smart factory has interoperable systems, multi-scale dynamic modelling and simulation, intelligent automation, strong cyber security, and networked sensors.

Contents

The broad definition of smart manufacturing covers many different technologies. Some of the key technologies in the smart manufacturing movement include big data processing capabilities, industrial connectivity devices and services, and advanced robotics. [5]

Graphic of a sample manufacturing control system showing the interconnectivity of data analysis, computing and automation. Graphic of a sample manufacturing control system showing the interconnectivity of data analysis, computing and automation Automated Manufacturing Research Facility.jpg
Graphic of a sample manufacturing control system showing the interconnectivity of data analysis, computing and automation. Graphic of a sample manufacturing control system showing the interconnectivity of data analysis, computing and automation
Advanced robotics used in automotive production BMW Leipzig MEDIA 050719 Download Karosseriebau max.jpg
Advanced robotics used in automotive production

Big data processing

Smart manufacturing leverages big data analytics to optimize complex production processes and enhance supply chain management. [7] Big data analytics refers to a method for gathering and understanding large data sets in terms of what are known as the three V's, velocity, variety and volume. Velocity informs the frequency of data acquisition, which can be concurrent with the application of previous data. Variety describes the different types of data that may be handled. Volume represents the amount of data. [8] Big data analytics allows an enterprise to use smart manufacturing to predict demand and the need for design changes rather than reacting to orders placed. [2]

Some products have embedded sensors, which produce large amounts of data that can be used to understand consumer behavior and improve future versions of the product. [9] [10] [11]

Advanced robotics

Advanced industrial robots, also known as smart machines, operate autonomously and can communicate directly with manufacturing systems. In some advanced manufacturing contexts, they can work with humans for co-assembly tasks. [12] By evaluating sensory input and distinguishing between different product configurations, these machines are able to solve problems and make decisions independent of people. These robots are able to complete work beyond what they were initially programmed to do and have artificial intelligence that allows them to learn from experience. [5] These machines have the flexibility to be reconfigured and re-purposed. This gives them the ability to respond rapidly to design changes and innovation, which is a competitive advantage over more traditional manufacturing processes. [13] An area of concern surrounding advanced robotics is the safety and well-being of the human workers who interact with robotic systems. Traditionally, measures have been taken to segregate robots from the human workforce, but advances in robotic cognitive ability have opened up opportunities, such as cobots, for robots to work collaboratively with people. [14]

Cloud computing allows large amounts of data storage or computational power to be rapidly applied to manufacturing, and allow a large amount of data on machine performance and output quality to be collected. This can improve machine configuration, predictive maintenance, and fault analysis. Better predictions can facilitate better strategies for ordering raw materials or scheduling production runs.

3D printing

As of 2019, 3D printing is mainly used in rapid prototyping, design iteration, and small-scale production. Improvements in speed, quality, and materials could make it useful in mass production [15] [16] and mass customization. [16]

However, 3D printing developed so much in recent years that it is no longer used just as technology for prototyping. 3D printing sector is moving beyond prototyping especially it is becoming increasingly widespread in supply chains. The industries where digital manufacturing with 3D printing is the most seen are automotive, industrial and medical. In the auto industry, 3D printing is used not only for prototyping but also for the full production of final parts and products. 3D printing has also been used by suppliers and digital manufacturers coming together to help fight COVID-19. [17]

3D printing allows to prototype more successfully, thus companies are saving time and money as significant volumes of parts can be produced in a short period. There is great potential for 3D printing to revolutionise supply chains, hence more companies are using it. The main challenge that 3D printing faces is the change of people's mindset. Moreover, some workers will need to re-learn a set of new skills to manage 3D printing technology. [17]

Eliminating workplace inefficiencies and hazards

Smart manufacturing can also be attributed to surveying workplace inefficiencies and assisting in worker safety. Efficiency optimization is a huge focus for adopters of "smart" systems, which is done through data research and intelligent learning automation. For instance operators can be given personal access cards with inbuilt Wi-Fi and Bluetooth, which can connect to the machines and a Cloud platform to determine which operator is working on which machine in real time. [18] An intelligent, interconnected 'smart' system can be established to set a performance target, determine if the target is obtainable, and identify inefficiencies through failed or delayed performance targets. [19] In general, automation may alleviate inefficiencies due to human error. And in general, evolving AI eliminates the inefficiencies of its predecessors.

As robots take on more of the physical tasks of manufacturing, workers no longer need to be present and are exposed to fewer hazards. [20]

Impact of Industry 4.0

Industry 4.0 is a project in the high-tech strategy of the German government that promotes the computerization of traditional industries such as manufacturing. The goal is the intelligent factory (Smart Factory) that is characterized by adaptability, resource efficiency, and ergonomics, as well as the integration of customers and business partners in business and value processes. Its technological foundation consists of cyber-physical systems and the Internet of Things. [21]

This kind of "intelligent manufacturing" makes a great use of:

European Roadmap "Factories of the Future" and German one "Industrie 4.0″ illustrate several of the action lines to undertake and the related benefits. Some examples are:

Statistics

The Ministry of Economy, Trade and Industry in South Korea announced on 10 March 2016 that it had aided the construction of smart factories in 1,240 small and medium enterprises, which it said resulted in an average 27.6% decrease in defective products, 7.1% faster production of prototypes, and 29.2% lower cost. [22]

See also

Related Research Articles

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Computer-aided design (CAD) is the use of computers to aid in the creation, modification, analysis, or optimization of a design. This software is used to increase the productivity of the designer, improve the quality of design, improve communications through documentation, and to create a database for manufacturing. Designs made through CAD software help protect products and inventions when used in patent applications. CAD output is often in the form of electronic files for print, machining, or other manufacturing operations. The terms computer-aided drafting (CAD) and computer-aided design and drafting (CADD) are also used.

<span class="mw-page-title-main">Automation</span> Use of various control systems for operating equipment

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Mechatronics engineering, also called mechatronics, is an interdisciplinary branch of engineering that focuses on the integration of mechanical engineering, electrical engineering, electronic engineering and software engineering, and also includes a combination of robotics, computer science, telecommunications, systems, control, automation and product engineering.

<span class="mw-page-title-main">3D printing</span> Additive process used to make a three-dimensional object

3D printing, or additive manufacturing, is the construction of a three-dimensional object from a CAD model or a digital 3D model. It can be done in a variety of processes in which material is deposited, joined or solidified under computer control, with the material being added together, typically layer by layer.

<span class="mw-page-title-main">FANUC</span> Japanese robotics company

FANUC is a Japanese group of companies that provide automation products and services such as robotics and computer numerical control wireless systems. These companies are principally FANUC Corporation of Japan, Fanuc America Corporation of Rochester Hills, Michigan, USA, and FANUC Europe Corporation S.A. of Luxembourg.

<span class="mw-page-title-main">Food industry</span> Collective term for diverse businesses that supply much of the worlds food

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DELMIA, a brand within Dassault Systèmes, is a software platform designed for use in manufacturing and supply chain professionals. It offers various tools encompassing digital manufacturing, operations, and supply-chain management, including simulation, planning, scheduling, modeling, execution, and real-time operations management.

The following outline is provided as an overview of and topical guide to automation:

<span class="mw-page-title-main">Rapid prototyping</span> Group of techniques to quickly construct physical objects

Rapid prototyping is a group of techniques used to quickly fabricate a scale model of a physical part or assembly using three-dimensional computer aided design (CAD) data. Construction of the part or assembly is usually done using 3D printing or "additive layer manufacturing" technology.

<span class="mw-page-title-main">Smart transducer</span>

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<span class="mw-page-title-main">Manufacturing engineering</span> Branch of engineering

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A vision-guided robot (VGR) system is a robot fitted with one or more cameras used as sensors to provide a secondary feedback signal to the robot controller for a more accurate movement to a variable target position. VGR is rapidly transforming production processes by enabling robots to be highly adaptable and more easily implemented, while dramatically reducing the cost and complexity of fixed tooling previously associated with the design and set up of robotic cells, whether for material handling, automated assembly, agricultural applications, life sciences, and more.

<span class="mw-page-title-main">STEP-NC</span> Machine tool control language

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The following outline is provided as an overview of and topical guide to production:

<span class="mw-page-title-main">Fourth Industrial Revolution</span> Current trend of manufacturing technology

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An intelligent maintenance system (IMS) is a system that uses collected data from machinery in order to predict and prevent potential failures in them. The occurrence of failures in machinery can be costly and even catastrophic. In order to avoid failures, there needs to be a system which analyzes the behavior of the machine and provides alarms and instructions for preventive maintenance. Analyzing the behavior of the machines has become possible by means of advanced sensors, data collection systems, data storage/transfer capabilities and data analysis tools. These are the same set of tools developed for prognostics. The aggregation of data collection, storage, transformation, analysis and decision making for smart maintenance is called an intelligent maintenance system (IMS).

Industrial and production engineering (IPE) is an interdisciplinary engineering discipline that includes manufacturing technology, engineering sciences, management science, and optimization of complex processes, systems, or organizations. It is concerned with the understanding and application of engineering procedures in manufacturing processes and production methods. Industrial engineering dates back all the way to the industrial revolution, initiated in 1700s by Sir Adam Smith, Henry Ford, Eli Whitney, Frank Gilbreth and Lilian Gilbreth, Henry Gantt, F.W. Taylor, etc. After the 1970s, industrial and production engineering developed worldwide and started to widely use automation and robotics. Industrial and production engineering includes three areas: Mechanical engineering, industrial engineering, and management science.

NIU College of Engineering and Engineering Technology was established in 1985 and offers ABET and ATMAE accredited programs in engineering and engineering technology. The college offers degree programs in electrical engineering, mechanical engineering, industrial and systems engineering, engineering technology, and industrial technology.

The industrial internet of things (IIoT) refers to interconnected sensors, instruments, and other devices networked together with computers' industrial applications, including manufacturing and energy management. This connectivity allows for data collection, exchange, and analysis, potentially facilitating improvements in productivity and efficiency as well as other economic benefits. The IIoT is an evolution of a distributed control system (DCS) that allows for a higher degree of automation by using cloud computing to refine and optimize the process controls.

<span class="mw-page-title-main">Fast Radius</span>

Fast Radius is a company that provides manufacturing services in four main areas: application discovery, product design and testing, production-grade manufacturing, and global fulfillment. Its on-demand manufacturing capabilities include additive manufacturing, or 3D printing, CNC machining, injection molding, and urethane casting.

References

  1. 1 2 Lu, Yuqian; Xu, Xun; Wang, Lihui (July 2020). "Smart manufacturing process and system automation – A critical review of the standards and envisioned scenarios". Journal of Manufacturing Systems. 56: 312–325. doi:10.1016/j.jmsy.2020.06.010. S2CID   225557967.
  2. 1 2 Davis, Jim; Edgar, Thomas; Porter, James; Bernaden, John; Sarli, Michael (2012-12-20). "Smart manufacturing, manufacturing intelligence and demand-dynamic performance". Computers & Chemical Engineering. FOCAPO 2012. 47: 145–156. doi:10.1016/j.compchemeng.2012.06.037.
  3. 1 2 SMLC 2011
  4. ↑ Shipp, Stephanie S. (March 2012). "Emerging Global Trends in Advanced Manufacturing" (PDF). Emerging Global Trends in Advanced Manufacturing. Institute for Defense Analysis. Archived from the original (PDF) on 2012-06-06. Retrieved 2020-04-12.
  5. 1 2 "On the Journey to a Smart Manufacturing Revolution". www.industryweek.com. 2015-12-30. Retrieved 2016-02-17.
  6. ↑ Albus, James S. (1995-01-01), English: Architecture for the NBS Automated Manufacturing Research Facility (AMRF). , retrieved 2016-03-04
  7. ↑ Rachuri, Sudarsan (February 4, 2014). "Smart Manufacturing Systems Design and Analysis" (PDF). National Institute of Standards and Technology. Retrieved February 16, 2016.
  8. ↑ Leveling, J.; Edelbrock, M.; Otto, B. (2014-12-01). "Big data analytics for supply chain management". 2014 IEEE International Conference on Industrial Engineering and Engineering Management. pp. 918–922. doi:10.1109/IEEM.2014.7058772. ISBN   978-1-4799-6410-9. S2CID   31872187.
  9. ↑ Yang, Chen; Shen, Weiming; Wang, Xianbin (January 2018). "The Internet of Things in Manufacturing: Key Issues and Potential Applications". IEEE Systems, Man, and Cybernetics Magazine. 4 (1): 6–15. doi:10.1109/MSMC.2017.2702391. S2CID   42651835.
  10. ↑ Porter, Michael E. (November 2014). "How Smart, Connected Products Are Transforming Competition". Harvard Business Review. April 2016.
  11. ↑ "Building Smarter Manufacturing With The Internet of Things (IoT)". IT World Canada. Lopez Research. 2014. Retrieved 2020-04-12.
  12. ↑ Wang, W.; Li, R.; Chen, Y.; Diekel, Z.; Jia, Y. (2019). "Facilitating Human-Robot Collaborative Tasks by Teaching-Learning-Collaboration From Human Demonstrations". IEEE Transactions on Automation Science and Engineering. 16 (2): 640–653. doi: 10.1109/tase.2018.2840345 . ISSN   1545-5955.
  13. ↑ "Robotic Systems for Smart Manufacturing". www.nist.gov. US Department of Commerce. October 2013. Retrieved 2016-03-04.
  14. ↑ Bicchi, Antonio; Peshkin, Michael A.; Colgate, J. Edward (2008-01-01). "Safety for Physical Human–Robot Interaction". In Siciliano, Bruno; Khatib, Oussama Khatib (eds.). Springer Handbook of Robotics. Springer Berlin Heidelberg. pp. 1335–1348. doi:10.1007/978-3-540-30301-5_58. ISBN   9783540239574.
  15. ↑ Zimmermann, Stefan (March 26, 2018). "Industry 4.0 – 3D Printing in Manufacturing Industries". Atos Blog. Atos SE. Retrieved 2019-06-09.
  16. 1 2 Hughes, Andrew (Mar 23, 2017). "Industry 4.0 is About More Than Data: 3D Printing in Manufacturing". Digital Transformation and Operational Excellence Blog. LNS Research. Retrieved 2019-06-09.
  17. 1 2 Wilson, Georgia (May 16, 2020). "The evolution of 3D printing in manufacturing". Manufacturing Global. BizClick Medial Limited. Retrieved 2021-06-04.
  18. ↑ "ThingTrax". ThingTrax Connected Manufacturing. London. Archived from the original on 2017-04-12. Retrieved 2020-04-12.
  19. ↑ Jung, Kiwook (2015-03-16). "Mapping Strategic Goals and Operational Performance Metrics for Smart Manufacturing Systems". Procedia Computer Science. 44 (44 p.184–193): 184–193. doi: 10.1016/j.procs.2015.03.051 .
  20. ↑ Louchez, Alain (January 6, 2014). "From Smart Manufacturing to Manufacturing Smart". www.automationworld.com. Automation World. Retrieved 2016-03-04.
  21. ↑ Jacinto, Joan (July 31, 2014). "Smart Manufacturing? Industry 4.0? What's It All About?". The Vault - Siemens Totally Integrated Automation.
  22. ↑ Jung Min-hee (March 11, 2016). "Smart Factories Improving Productivity of SMEs".
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