Smart Factories (also known as Connected Factories) have many definitions. One way to define them is a group of technology innovations. When used together, these innovations support consolidated, connected, and flexible manufacturing processes. The processes run manufacturing, supply chain, and related back-office operations.
Smart Factories enable machines and people to make intelligent decisions, which result in automated or human actions. Some definitions include smart factories reaching "self-optimizing operations." In these cases, the factory continuously adapts to demand and variations in supply and corrects processes that exceed tolerances.
Another reason to build smart factories is that employees responsible for monitoring and controlling production lines can do so remotely with less human attention. Factories can now adapt to the workflows in real-time by machines communicating with other devices and humans.
How would one recognize a smart factory?
Usually, a Smart Factory will define by its core functions, which include:
- Digital connectivity across shop floor
- Intelligent automation and decision making
- Cloud-based data management and analytics
Digital connectivity: Smart factories use sensors and other devices to collect production equipment data and send to the Internet of Things (IoT) via specific protocols for storage and further analysis. The insights extracted from the data enable monitoring production, logistics, and product design processes throughout the shop floor facility and beyond. This sensor-driven capability increases the awareness of what is happening at several levels of factory operation. For example, traditionally vibration sensors provide alarms that indicate when bearings, motors, or machines need to be shut down. Now the deep insights of the data pattern could enable predictive maintenance actions that avoid larger production problems that would occur if the abnormal condition were left unattended. With smart sensors, factory staff members can work with suppliers, partners, and customers more effectively. These sensors and sensor-embedded devices can, in turn, connect to a global system of similar process systems and digital supply chains through the factory, warehouses, and offices.
Intelligent automation: This umbrella term includes advanced robots, machine vision, distributed control processes, and drone technologies. Industrial robots detect and avoid people and other unexpected obstacles as they work. Avoiding such common disruptions is a huge advantage that can prevent production delays and downtime. Ultimately, automation applies intelligence at the factory level and creates a dynamic production environment, which improves product quality and reliability. Automated processes also involve intelligent agents and other cyber-physical systems to operate more efficiently and distribute manufactured goods more quickly in response to market demand. Smart equipment makes it possible to automate much of what is required to produce smaller-sized manufacturing runs. Minimizing downtime for recalibrating and resetting equipment makes manufacturing more customizable and helps manufacturers respond more quickly to changing market tastes.
Cloud-based data management and analytics: The industrial Internet of Thing (IIoT) is the global network of internet-connected, physical objects, and devices used in the industrial environment based on cloud infrastructure. The IIoT enables these objects to communicate with each other and with nonindustrial, internet-enabled devices and systems.
Facility-wide communications and the ability to use manufacturing data is what makes factories smart. New technologies are developing and converging to create smart factories possible. Smart factories connect production hardware, processes, and humans with data provided by sensors connected to the Industrial Internet of Things throughout factories and beyond. By combining all parts of the production process, a manufacturer can streamline and speed up building and testing products across every platform. In smart factories, all industrial assets are connected in the same facility and between production facilities. At each stage of production, sensors exchange data in real-time, and data analytics applications monitor operations to ensure ideal process performance. The evolution of smart factories is trending towards data-based management cultures and fully autonomous operation. Developing independent operation requires that plant managers change their perspective from a go-it-alone, problem-solving culture to a monitor-and fine-tune process culture. This type of change is often overlooked and undervalued. Manufacturers need to expect current organizational structures to be a significant obstacle to attaining smart factory design and process goals.
Identifying the pillars of smart factories
In both concept and capabilities, smart factories go beyond the conventional definitions of automated plants. Industry 4.0 principles recognize nine key technologies, which manufacturers can use to improve many production processes.
- Industrial Internet of Things
Manufacturers attach sensors to physical assets located on the plant floor and then connect it to the worldwide control and measurement devices. This variation on the IoT connects devices, machines, data management software, process optimization applications, productivity software, and humans. The objective is to collect data that influences decisions (often in real-time), making production more efficient and making more accurate decision-making.
- Augmented reality
Unlike the all-digitals of virtual reality (VR), augmented reality (AR) uses a device, such as a mobile phone or special eyeglasses to display real-world digital content. AR can display data, instructions, or holographic images, atop a user's real-world appearance of workstations, equipment, production lines, or warehouse locations.
- Cyber-physical Systems
Manufacturing design, production, and logistics processes create mountains of data. Cyber-physical systems are computer systems in which machines will design, controlled, or monitored by computer-based algorithms. System data create models, which reflect the physical aspects of product development and production processes in a virtual environment. Engineers use CPS models to simulate, test, and improve machine processes and settings before production starts. The desired result: to reduce process downtime, reduce product development time and costs, and improve overall product quality.
- Additive Manufacturing (AM)
Manufacturers are expanding the use of additive manufacturing (3D/4D printing) in their product design and production processes. It already plays a vital role in product design, prototyping, and low-volume production.
- System integration
In Industry4.0 systems, connectivity is the bedrock of integration. Currently, many manufacturing information systems are not operating in an integrated manner. With improved system integration, all aspects of a manufacturing company—machines, devices, humans, and cyber-physical systems—can become interoperable, within and beyond smart factory walls. Most importantly, the integration will create an agile manufacturing environment, enabling real-time process corrections and more responsive processes.
- Cloud computing
As manufacturers use more information technology and share more information in smart factories, hosted computing services provide almost unlimited data storage and computing power. Cloud-based computing services also help manufacturers make computing more scalable, data more accessible, and data cleaner and safer to use.
- Autonomous robots
Although genuine autonomy is still a goal, not reality, this class of advanced robots performs tasks that require capabilities between automated robots and human workers. In some ways, automated production robots design to work like humans, but they have the added ability to monitor and transmit data.
As digital connectivity increases, the risk of a potential cyberattack, and data loss threat grow with it. Any security breach could damage several factory operations areas, from the supply chain to production to the company's loss of reputation. Companies must prepare and protect their information systems, sensitive data, and production lines from cyber threats.
- Big data analytics
There are massive amounts of untapped data in the manufacturing industry, and factory owners are just beginning to learn how to use it. The common theme among all smart technology pillars is data collection and analysis. High-volume, high-speed data collection and research have been available for more than five years. Big data analytics, cybersecurity-related pattern recognition, and inventory control are just three of many ways that data analytics contribute to more efficient factory operation.
- Human talent
Industry 4.0 experts encourage manufacturers to look beyond efficiency and new business models. Their advice: invest in human talent as well as manufacturing infrastructure. Manufacturers should welcome data specialists to thrive in the approaching digital manufacturing environment and become a vital part of its long-term success. Human talent also needs the support of new tools and practices. Decision-makers will need help to recognize business opportunities as well as work more efficiently. Dashboards and other data and analytical tools can help specialists clean, organize, and present massive volumes of available data.
Smart Factory Benefits
After smart factory connectivity, sensors, and intelligent decision-making technologies are installed, configured, and tested, one question remains. Will manufacturing processes improve? Will adding smart manufacturing systems to fabrication and assembly fundamental methods make manufacturing more efficient and workers more productive?
Advanced capabilities lie at the heart of process improvements. These capabilities include:
- Streamlined data discovery and collection: Smart technologies automate data collection and provide advanced production data analytics. These capabilities help managers make faster, more informed decisions. In a smart factory, connecting operations technology and business systems enable manufacturers to measure their key performance indicators against their high-level business goals.
- Predictive maintenance: With better monitoring of data and devices, manufacturers can predict and fix maintenance problems before causing downtime or product quality issues. For example, sensors connected to machines or devices can send condition monitoring or repair data in real-time. This way, manufacturers can identify and fix problems much more quickly.
- Less waste, more accurate forecasts: When operations and enterprise systems are connected, manufacturers can identify waste and make more accurate forecasts. Managers get a better understanding of demand levels and supply chain problems. With this information, factory operators can avoid costs related to excessive inventory or unexpected production volume.
- A faster, more accurate view of supply and demand: Smart, connected systems help manufacturers understand their operations and data. In a smart factory, digital connectivity gives manufacturers a clear, complete, and accurate view of bottlenecks, machine performance problems, and other operational inefficiencies. With this data, manufacturers can adjust yields, improve product quality, and reduce waste.
- Delegating routine tasks to robots: Improvements in automated decision-making machines (robots) make it possible for humans to intervene less and less in production processes.
Benefits: Essential Process Improvements
The single, most essential benefit that smart factories provide is enabling their operations to do more—give leaner processes, more flexible product development, and more agile responses to technical and market changes. The advanced capabilities we describe above make these process improvements possible:
- Lower product design and development costs: 3D printing supports rapid prototyping and testing of new designs. By using agile development methods, manufacturers can use "fast fail" Agile methods to design and test new or upgraded products.
- Lower operations costs: Smart manufacturing provides greater data access across the supply chain by defining which resources are needed and when real-time data enables manufacturers to reduce overstocking costs or shortfalls. Smart processes shrink the volume of waste and avoid system downtime by supplying just the number of parts that are is needed, neither more nor less.
- Lower capital costs: Increasingly, smart factory design includes production systems suited to different setups or more than one task–a robot that can drill and weld, for example. Using versatile multi-task assembly machines with fewer chassis can provide significant CAPEX savings.
- Lower labor costs: Delegating some assembly, inspection, and decision-making duties to robots and automated assembly robots can reduce total human effort and labor costs.
- More agile manufacturing: Using data analytics and embedded sensors, smart factory logistics systems automatically compare demand levels and production rates. By using this capability, manufacturers can control throughput and respond quickly to changes in market conditions.
By Colin Koh, Senior Business Development Manager, Industry 4.0 Consultant of LKH Precicon
Colin is a technology evangelist, digital transformation specialist, and highly-respected figure in the ASEAN business community, who previously served as the President of the Singapore Industrial Automation Association (SIAA), is a certified IoT specialist and an MIT Sloan School of Management Executive program in Artificial Intelligence and IoT. Colin currently provides mentorship and advisory to companies implementing digital transformation towards Industry 4.0.