With lean manufacturing, businesses can maximize productivity while minimizing waste. Lean principles can be difficult to implement, however, especially for businesses without the right data.
IoT data analytics can help make lean manufacturing much more practical. The right combination of smart sensors and monitoring devices can provide information that businesses need to streamline operations and reduce waste.
What IoT Devices Can Bring to a Lean Manufacturer
IoT devices, along with other Industry 4.0 technologies, are some of the most valuable data-collecting tools that modern manufacturing has.
With the right device, it’s possible for a manufacturer to collect a massive variety of data — including information on the manufacturing process, the movement of goods through a facility and the performance of essential equipment.
Specific IoT devices can collect information on temperature, humidity, movement, ultrasonic sound and other vibrations. These devices are connected to the internet and can deliver information to multiple locations continuously.
The same device or IoT system, as a result, can supply information to an automated factory management system, send updates to managers and store data for later review.
Many IoT devices are also directly integrated with AI or big data analytics systems that allow businesses to take full advantage of the vast quantities of information they can collect.
Lean manufacturing often works best when data on the production process is easy to obtain and analyze.
IoT devices can offer lean manufacturers a real-time view of important manufacturing processes. By gathering information on these processes, managers can more easily identify sources of waste, inefficiencies and opportunities to maximize productivity.
Different Use-Cases for IoT Devices in Lean Manufacturing
IoT devices can be deployed in various configurations or combinations to support most of the key principles of lean manufacturing.
For example, eliminating waste is a principle of lean manufacturing, but waste isn’t always obvious.
Certain types of waste, like overproduction, can also be difficult to manage once uncovered, as this waste may be generated by a variety of oversights or miscalibrations in the manufacturing process.
By using different IoT devices, it’s possible to automatically identify and mitigate a wide variety of waste-causing manufacturing errors.
Improving Worker Safety
Many manufacturing processes, unintentionally, overtax both staff and site hardware. Excessive overtime, for example, is a common result of worker mismanagement and can easily lead to mistakes, dangerous working practices and compromised worker safety.
These practices, in addition to being dangerous, are also wasteful. Low safety typically leads to high turnover rates, mistakes require rework and accidents can have long-term consequences for both individual workers and a job site.
IoT can also help to make manufacturing processes both more efficient and optimize workloads, helping ensure that labor is well-distributed and excessive overtime isn’t common or possible.
Other devices may directly monitor how employees are working, allowing them or their managers to make adjustments to workstyle or workflow that will reduce unnecessary strain.
For example, some businesses are pioneering wearable haptic sensors that can detect and mitigate workplace injury. These sensors are small IoT devices that workers can wear on their body. The device provides haptic feedback, or vibration alerts, when workers move in a way that may cause strain, stress or musculoskeletal injury.
Information on worker movement gathered by these sensors can also be delivered to data dashboards and IoT analytics much like data from other IoT devices.
Minimizing Unnecessary Wait Time and Analyzing Manufacturing Flow
Many manufacturers struggle with wait time — products or components that spend a great deal of time waiting before they move to the next step of the manufacturing process.
Motion detectors, video cameras, heat sensors and other smart devices can be used by manufacturers to track the movement of goods, allowing them to monitor wait time throughout the production process.
Managers can follow along this data in real-time, giving them a deeper understanding of how goods flow through the manufacturing process and mistakes that may be increasing wait time or generating other kinds of waste.
Similar devices are also used in the supply chain to monitor the flow of goods and optimize logistics processes.
Information from these devices can be sent to multiple endpoints, including cloud storage, analytics platforms and data dashboards. Analytics platforms can automatically and continuously analyze timing data, alerting staff if needed when anomalous wait times are detected.
Dashboards provide human-readable data that managers can use to pinpoint inefficiencies and spot process bottlenecks.
Cloud-stored data can be used for record-keeping, or employed as historical data for training AI algorithms and generating reports. Because this data can be reviewed at any time, it may also be useful for determining trends and identifying if a problem has become worse over time.
Integrate Different Processes
IoT devices can also make it much easier to bring together disparate parts of the manufacturing process — especially operational technology (OT) and information technology (IT).
For example, IoT devices can help remotely control or collect information on the performance of machines, offering real-time information to OT staff and IT integration opportunities.
The same IoT system can help to make new maintenance strategies possible — like predictive maintenance — while also encouraging communication between IT and OT systems.
Information from IoT systems can also be used to identify process inefficiencies and optimize production. With the right analytics tool, managers can correlate waste or certain types of error to specific machines or steps in the manufacturing process — making it easier to pinpoint where waste is being generated during manufacturing.
Using IoT Devices to Implement and Improve Lean Manufacturing
IoT devices can provide manufacturers with a real-time view of manufacturing processes, making it easier to optimize work and cut down on waste.
A fleet of devices can gather a massive amount of information relevant to lean principles, including data on worker safety, wait times and machine performance.
Data from IoT devices can be made even more useful with advanced analytics platforms that may use technology like big data analysis or machine learning.