Enabling technology, the combination of connectivity, intelligence, and flexible automation, is required for smart manufacturing. While “smart manufacturing” is a concept rather than a process that can be directly implemented, according to a recent report from MarketsandMarkets, the smart manufacturing market will be worth US$299 billion by 2023, growing at a CAGR of 12% between 2018 and 2023. The report is entitled “Smart Manufacturing Market – Global Forecast to 2023.”
Attractive Opportunity in Smart Manufacturing Market
Data is at the core of growth of smart manufacturing where data will decide what to do and when to do it. Analysis of these data will help in making the production process efficient. Companies are constantly investing and exploring the benefits from these enablers, said Sachin Garg, Associate Vice President, MarketsandMarkets.
Some of the prominent enabling technology in today’s manufacturing ecosystem are mentioned below. Other IT related technology includes Human Machine Interface, Enterprise Manufacturing Intelligence, Plant Asset Management, Manufacturing Execution System, Industrial Communication, and Warehouse Management Systems.
These technologies are yet to evolve and be adopted at full scale by the manufacturing ecosystem. However, they may bring big changes in the way manufacturing is being carried out.
Engineers used to create scientific models to understand real-world problems. During the early days of industrialization, this was comparatively eas. But as machines become ever more sophisticated, so does their modelling. Creating digital twin models has been happening for almost 50 years, but it’s only now being done on a large scale. This is mainly because of innovation and advancement in sensor and network technology, which helped in digitalizing any existing or new model. Other technologies that complement digital twinning are Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and Augmented andVirtual Reality (AR/VR).
Blockchain in Manufacturing
Blockchain is still at a nascent stage of development, but it has huge scope in manufacturing ecosystems. Blockchain ensures that wherever there is a transaction, that transaction is validated, recorded, and secured. Supply Chain and smart contracts are some of the important applications of blockchain in manufacturing. The blockchain market in manufacturing has yet to evolve fully. The market should start generating significant revenue from 2020 onwards.
Automated Guided Vehicles
Automated guided vehicles (AGVs) are used for automated handling of materials. AGVs safely handle and transport all kinds of products, eliminating the need for human intervention in production, logistics, and warehouse environments. AGVs can increase the efficiency and productivity of material handling operations. Now, many AGVs are also equipped with robotics-related accessories, which eases implementation and allows great application of the technology.
Smart manufacturing is all about data, so all the equipment, component and systems implemented under the ecosystem of smart manufacturing is driven by data. To protect these data, organizations should implement robust industrial cybersecurity. Advanced cybersecurity products provide comprehensive security to critical infrastructure and ensure confidentiality and integrity of the system.
Industrial Machine Vision
Industrial machine vision is a combination of mechanical, optical, electronic, and software systems used to detect defects in objects, surfaces, materials, and manufacturing processes. Machine vision in smart manufacturing ecosystems helps improve quality, and increase flexibility while improving operational efficiency. Machine vison coupled with robotics systems and Artificial Intelligence will further help in strengthening the manufacturing systems under the concept of smart manufacturing.
Machine Condition Monitoring
Machine condition monitoring is the process of determining the operational state and condition of a machine to detect potential breakdowns with the help of automation. Machine condition monitoring optimizes equipment readiness and reduces maintenance and staffing requirements. It is used to prevent unscheduled outages, reduce downtime, and optimize machine performance. This technique is primarily classified into preventive machine monitoring and predictive machine monitoring. Predictive monitoring allows companies to detect potential trouble, diagnose problems, and choose remedial actions before downtime occurs.
Artificial Intelligence in Manufacturing Market
Collaborative robots, or co-bots, and predictive maintenance are just two AI applications for manufacturing. Co-bots that are designed to work alongside humans in a workspace to provide enhanced efficiency. These robots are different from industrial robots in a number of ways, such as the absence of “safety fence” while working alongside humans, simplified programming and reduced setup time. Implementation of AI in Co-Bots will further strengthen their ability to work successfully with humans.
Industrial 3D printing is used in various applications such as tooling, robotics, and special machinery. Robotics forms an important part of industries such as automotive, aerospace and defense. Industrial 3D printing simplifies the expensive and time-consuming process of manufacturing tools, eliminating assembly lines and thereby reducing labor costs as well. Industrial 3D printing is also used for developing special machinery such as heavy equipment and machinery components.
In addition to historical trends and forecasts, the report highlights some key players, including ABB, Cisco, Emerson, GE, Honeywell, IBM, Oracle, PTC, Rockwell, SAP, Schneider, Siemens, and Yokogawa.