What is Industry 4.0?
Industry 4.0 manufacturing comprises a variety of technology concepts that are powering the next industrial revolution through the cloud, Industrial Internet of Things (IIoT), digital twins, edge computing, and other concepts of technology, for example cyber-physical systems (CPS) and machine-to-machine communication (M2M).
The automation of technology powers industry 4.0, enabling industrial and manufacturing practices to become more efficient.
The IR4 technology is designed to integrate conventional discrete systems like software and hardware that give transparent information/data, decision decentralization, and augmentation of the decision-making process within technological systems to decrease the interference of humans.
Industry 4.0 for Lean manufacturing
Lean methodology is a production process that aims to emphasize efficiency through the elimination of waste. The lean manufacturing system philosophy works seamlessly with Industry 4.0 innovations that help the production department in saving money, time, money, materials, energy, and human capital. It mainly helps in the deployment of various IR4 techs.
The manufacturing companies which implement industry 4.0 tech can save time and money by using sensors and other IIoT devices to perform predictive and prescriptive maintenance, maximize machine utilization, quickly respond to fluctuations in the market, identify bottlenecks, mitigate safety issues, make real-time choices based on visualized data, increase the visibility of shop floor, warehouse space optimization and costs of overhead. It helps to take strategic and informed decisions. The possibilities for implementation are endless if manufacturers can build the infrastructure to support the collection and transformation of data.
Human to Machine
The most obvious way to collect human-machine data is through digital interfaces. The CPS can transcribe data into a database using conventional practices such as typing into a computer as well as on tables., to communicate with its operators. Alternatively, it can share information through advanced methods of data collection. For example, computer vision could be used to collect specific gestures or movements as data.
Machine to Machine
In the past, communication between 2 machines has typically involved a machine pushing data into another machine. This type of communication has been achieved using an Ethernet connection. Siloed proprietary technology has limited the full potential for machine-to-machine communication.
Data Acquisition & Processing
Manufacturers may use a variety of software to manage their operations, including enterprise resource planning (ERP) systems for managing purchases and financial planning, manufacturing execution systems (MES) to track and trace materials, and employee relationship management (ERM) software to manage their employees.
Production systems are often massive and siloed, which makes it difficult to access data. Manufacturers should use CPS to take more useful data to combine it and deliver an interconnected and holistic vision for the production.
How to stay lean with 4.0
When businesses are adapting Lean manufacturing with industry 4.0, they should start it on a small scale. Before implementing the tech they should give the proper training to the engineers, ground-level workers, and plant managers. For making it more productive, the manufacturing companies should plan the processing, do the data collection and find the areas for improvement.
Design to learn
The primary step to design a digital system for data collection is to develop a workflow process. Because lean 4.0 processes are continually evolving, benchmarking data will reveal flaws in the existing system.
Manufacturers must create a flexible development process that can customize to their needs. To test the process, they should start with small-scale implementations and ensure that both the business benefits and development costs are as expected.
Collect data from the test
Take the initial test of the new technology lives into production. When testing a new process, ensure you collect data that can give the right insights where the elements can be adjusted for the success of the test.
For example, identifying challenges of technology and culture in case the operator is struggling to understand. Track production levels to identify any short-term issues.
Scale through iteration.
Under Lean 4.0, continuous improvement is enabled by technology; however, the iterative process—the application of learnings based on testing at a pilot plant to other lines and the application of conceptual learning to other areas—is what makes the continuous improvement process truly continuous.
The Future of manufacturing
The use of a variety of new technology enabled by Industry 4.0 is creating a leaner manufacturing process. The key to these solutions lies in extracting data from operations and using it to make better, faster decisions across the business, such as those involved in maintenance, quality, production, or the entire plant.
