As part of Industry 4.0, key technologies, and concepts such as industrial Internet of Things (IIoT), cloud computing, edge computing, digital twins, machine-to-machine communication (M2M), and cyber-physical systems (CPS) are included.
Automated processes are at the heart of the Fourth Industrial Revolution. Industrial and manufacturing processes can become more efficient and self-sufficient by using a variety of data collection and communication systems.
As part of Industry 4.0, technology connects disparate systems using hardware and software, makes information transparent, contributes to decision-making through aiding human decision-making, and decentralizes decision making within technological systems so that humans are less likely to intervene.
Manufacturers are working to become more efficient and nimbler by adopting lean manufacturing practices. It may be difficult to implement lean approaches due to their complexity and lack of visibility, despite their significant benefits. This could be improved by Industry 4.0.
What Does Industry 4.0 Mean for Lean Manufacturing
Lean manufacturing has become popular among manufacturers, aimed at eliminating waste and becoming more agile by eliminating activities that add no value to the process. Lean manufacturing is used in many industries in order to improve their operations continuously.
Lean manufacturing benefits from Industry 4.0 in ways that save time, money, energy, material resources, and human resources, particularly when multiple industry 4.0 technologies are applied simultaneously.
Industrial 4.0 and Lean can be complimentary, and each can provide manufacturing and operations managers insight into increasing production efficiency. Many refer to it as 'Lean Industry 4.0'.
The use of sensors and other IIoT devices reduces downtime for manufacturers that use Industry 4.0 technology, maximizing machine utilization through predictive and prescriptive maintenance. Pivot quickly and innovate in response to market fluctuations, identify and mitigate bottlenecks, make real-time decisions, increase visibility on the floor, optimise warehouse space, and other data sources.
Factory production lines are no longer siloed; industry 4.0 enablers such as integration power production managers manage interconnected networks of moving parts, which can identify opportunities for improvement and even be trained to optimise performance. Lean improvement activities are directly affected by this increased visibility.
How Lean and Industry 4.0 converge?
Customer Centricity
A customer-centric approach to production has always been at the core of Lean, and digital technologies are now allowing manufacturers to better understand their customers' needs.
Continued Improvement
Manufacturers can now test their assumptions in the virtual world before implementing or testing them in the real world with powerful simulation tools and digital twins with the help of New 4.0 Technologies. This helps to achieve continuous improvement in the lean manufacturing approach.
Value Chain that is Integrated
Lean tries to reduce waste all along the value chain, from client order to delivery, and industry 4.0 enablers like data analytics and system integration can help. Integrated and connected enterprise systems, IT systems, operational systems, machines, and devices provide a holistic view of the complete value chain. By analysing this data, managers can identify patterns or weak points in their processes and prioritize where to improve.
The benefits of Industry 4.0 for Lean Manufacturers
Smart factories have become one of the most important trends of the Fourth Industrial Revolution, and they showcase countless technologies that will define the coming decade. As a result, vertical and horizontal value chains are being digitalized. Listed below are examples of Industry 4.0 solutions used in smart factories by lean manufacturers. Our guide provides a full list of solutions for smart factories, including:
Data for continuous improvement
Continuous improvement is central to lean manufacturing. If manufacturers intend to improve their processes, they need to know where the improvements can be made. The data from connected machines and sensors throughout the workplace can be used to provide Industry 4.0 with this information.
With IIoT devices, workplaces can build digital twins of their work environments. Digital models represent physical systems, such as the equipment on the manufacturing floor. By monitoring and connecting the entire production floor, cyber-physical systems can allow automated choices to be made based on data. These cyber-physical systems allow machines to communicate with each other, as well as with humans.
In this digital twin, each process is visualized as it affects productivity or quality overall, thereby showing where improvements are needed. After identifying which areas require improvement, manufacturers can utilize the digital models to determine the best course of action.
Efficient Maintenance and Increased Machine Uptime
While continuous improvement is based on past data, Industry 4.0 offers insights in real time. IIoT networks can deliver data as it is being collected, alerting workers to important readings or events as they occur. Real-time visibility is another lean principle that provides faster incident response, reducing disruptions and wasted efforts.
Maintenance schedules for these sophisticated systems are developed based on the information collected by sensors and machine interface connectors, which is then evaluated to ensure maximum resource utilization. The benefit to this is that unlike preventive, usage-based maintenance, parts aren't replaced when they still have significant life left. Additionally, replacement of parts is a prerequisite to ensuring that quality remains high or that long-term or expensive damage is avoided to machinery. Prescriptive maintenance insights also include suggested solutions to difficulties when optimizing towards a specific KPI (or set of KPIs), such as waste reduction or speed.
Many production problems can be solved if personnel respond quickly enough. That's a huge difficulty without continuing data collecting, because personnel don't have the time to constantly monitor every unit. That difficulty is solved by Industry 4.0, which collects data automatically and alerts workers to problems as they develop.
Improved Asset & Inventory Visibility
Lean manufacturing also involves inventory management, which is important but difficult. Maintaining a low inventory level is necessary to prevent waste, but this requires a high level of visibility into existing and incoming requirements. As a result of Industry 4.0, you can maintain a low inventory level and fulfil demand at the same time.
Industry 4.0 technologies, such as radio frequency identification (RFID) and Bluetooth Low Energy (BLE), provide real-time data about inventory numbers and locations. The real-time data shows producers how much inventory they can reduce as a result of just-in-time manufacturing. Manufacturers can make adjustments to their inventory as demand fluctuates over the course of a year as the data indicates emerging trends.
This inventory insight can also help to cut down on time waste in activities such as picking. Workers can use RFID or BLE devices to locate the exact location of any essential objects, allowing them to be retrieved faster. The results are spectacular, with some picking times reduced by 50-60% or more.
Better and transparent Quality Control
Industry 4.0 also makes quality control more effective. Industry 4.0 technologies like machine vision systems can detect faults faster and more accurately than humans by comparing goods against data about quality. By eliminating errors before they even occur, connected technologies can go much further.
It can be used to identify what is causing problems by using data from every machine in a workflow. As a result of interconnected systems, they can detect trends in product quality over time, helping pinpoint problematic areas. Manufacturers can address critical issues with contextual data and modify operations to eliminate defects at the source.
The more these analytics solutions are employed by manufacturers, the more accurate they will become, similar to many other data-driven applications. With more data, the results are more precise. By implementing more IIoT technologies, manufacturers can resolve issues sooner and more accurately.
Edge Computing
A key component of edge computing is distributed computing resources, which are typically close to data collection points, as opposed to cloud computing. By being able to evaluate data decentralised within the plant, the plant can produce insights more quickly, ideally in real time.
The speeds of edge computing are fast enough to prevent machines from malfunctioning in the event of a safety threat, and they are virtually invisible to humans in real-time. In order to prevent equipment breakdowns and downtime, predictive and prescriptive maintenance are frequently used.
Let’s wrap up
Lean manufacturing, which is a highly useful objective, is extremely difficult to implement with traditional processes. Those advantages are now available thanks to Industry 4.0, which enables firms to take advantage of lean processes to their fullest. Lean can certainly be achieved without these tools, but the process is much more difficult and produces far fewer significant results.
New technologies are bringing Industry 4.0 to the fore, making manufacturing leaner and more efficient. The basis of these solutions is gathering and analyzing data from operations to guide better, faster decision-making across an organization, whether you're in charge of maintenance, quality, production, or the entire facility.
By starting with the basics and focusing on the heart of the operation (the machines and people on the shop floor), you may set the stage for a more intelligent, more connected lean operation.
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