The fourth industrial revolution has a profound and lasting impact on global manufacturing. By combining technologies (such as the internet of things (IoT), cyber-physical systems (CPSs), and artificial intelligence) and devices to ensure seamless connectivity, interoperability, visibility, and intelligence capabilities, it has revolutionized the manufacturing process, leading to smart manufacturing.
The resulting Smart Manufacturing promises self-sufficient manufacturing processes, where machines and devices interact with each other through digital connectivity without, or with minimal, human control.
These smart factories merge physical and advanced cyber technologies such as artificial intelligence (AI), robotics, big data analytics, 3D printing, and cloud computing, making them much more intricate and accurate, improving performance and quality controllability, management, automation, and transparency of manufacturing processes.
A smart factory represents a leap from more traditional automation to a fully connected and flexible system. It enables manufacturers to integrate the floor decisions and perceptions with the supply chain. In other words, a smart factory is a flexible ecosystem that can self-optimize, self-adapt, and learn from new factory conditions in real or near-real time, and autonomously run entire manufacturing. Many manufacturers are already leveraging a smart factory’s advanced planning and scheduling components, using real-time production and inventory data.
Although a lot of research has been carried out focusing on analyzing the performance, processes, and implementation of smart factories, most companies still lack in-depth insight into the difference between traditional and smart factory systems. This article provides a broad overview of the differences and the variations between traditional and smart factories.
Smart factory vs. traditional factory
To meet drastic changes in customer demands, manufacturers require abilities that help adjust product type and production capacity to handle multiple product varieties. They should have adequate functionality, scalability, and connectivity with customers and suppliers to meet such challenges.
Traditional factories lack these capabilities to monitor and control automated and complex manufacturing to enable efficient production of customized products. Instead, they have stand-alone and segregated applications with less integration, product life cycle, and value chain. Consequently, there is poor reuse of systems and integration between real and digital systems for a series of distinct and independent steps in a traditional set-up, including marketing, product development, manufacturing, and distribution.
On the other hand, a smart factory is an upgrade from old-fashioned automation to a linked and flexible system, which constitutes a continual data stream through highly connected operations and production systems that can learn and adapt to changing demands. These factories can assimilate data from physical, operational, and human assets to drive manufacturing, maintenance, inventory tracking, digitization of operations, and other manufacturing systems activities. Smart factories aim to use intelligent production systems and suitable engineering methods to successfully and interconnected production facilities.
It is an engineering system that operates on interconnection, collaboration, and execution. Interconnecting devices in smart factories allow the exchange of information, recognize and assess situations, and integrate the physical world with the digital world, making smart factories adaptive in nature.
In other words, the smart factory integrates physical and digital technologies and makes the involved technologies more accurate, enhancing the performance, quality, controllability, management, and transparency of the manufacturing processes. In such a smart factory environment, the manufacturer can meet customer requirements by changing the machines’ production specifications and other settings at the last minute. This ability is not present in traditional factories. The ability to tailor and learn from real-time data makes smart factories more predictive and receptive to avoid operational downtime and other possible failures in processes.
A smart factory’s true feature lies in its capability to readjust and evolve along with the organization’s growing needs. These needs are categorized into changing customer demands, developing new products and services, emergence of new markets, enhanced productive approaches to operations, and use of advanced technologies in maintenance processes.
Let’s now look at the key differences between the traditional manufacturing factory and smart factory.
- Manual and isolated processes and operations. No integration with different systems and tools.
- Legacy systems with frequent machine failures and increased maintenance costs.
- Tied to systems or machines for data, therefore zero or limited data for decision making; process-driven decision making.
- Limited technology involvement.
- Zero or limited visibility on operations and productivity data.
- Limited innovation in production development.
- Inaccurate asset tracking process, poor interoperability, and resource utilization.
- The production line is fixed unless it is manually reconfigured.
- Highly automated production and material handling with less human intervention.
- Digitized and integrated processes and operations with improved machine utilization and reduced maintenance costs.
- Complete integration with existing and new systems and tools.
- Increased transparency and visibility on operations and production data.
- Accurate asset tracking using IoT and RFID.
- High interoperability.
- Reliable, predictable production capacity and increased asset uptime and production efficiency. Minimized cost of quality and production.
- Live metrics to support quick and consistent decision making.
- Real-time collaboration with suppliers, customers, and departments (e.g., feedback from production to product development)
- Predictive anomaly identification and resolution. Real-time safety monitoring.
A smart factory is characterized by these key features:
Modularity: This refers to system components’ capability to be coupled and reconfigured easily and quickly on a plug-and-play principle. The smart factory should possess high modularity, allowing the rapid integration of modules that can be added, rearranged, or relocated in the production line on time. This allows the system to respond to changing customer requirements and to overcome internal system malfunctions.
Interoperability: This is the interconnection and coordination between different devices and system components, allowing flexibility in configuration protocols of the production system and communication between manufacturing enterprises and customers.
Decentralization: This is the ability of the system elements (modules, material handling, products, etc.) to make decisions on their own in real-time, unsubordinated to a control unit, without violating the overall organizational goal, and to interact with their environment via sensors and actuators.
Integration: Robots, sensors, and artificial intelligence (AI) allow smart factories to have a high integration level among processes. Artificial intelligence, along with the integration of human intellectual capabilities, enables factories to perform analysis and decision making.
Virtual reality (VR): VR is one of the high-level components of smart factories. It facilitates human-machine integration by virtualizing manufacturing processes using computers, signal processing, animation technology, intelligent reasoning, prediction and simulation, and multimedia technologies.