In recent years, the use of data in the manufacturing industry has grown significantly, especially when solving challenges related to manufacturing processes and technology succession issues. With that being said, some on-site managers worry that they are collecting a large amount of data without knowing how to use it efficiently.
In this blog, we’ll discuss common challenges faced by manufacturing organizations, solutions to these challenges, and the benefits of using data correctly. Understand why data utilization leads to improvements in manufacturing and how to implement data utilization for your company.
What is data utilization in the manufacturing industry?
In the manufacturing industry, data utilization means leveraging the data generated and accumulated within the company to improve productivity and quality.
At manufacturing sites, data is collected from various sensors to visualize the operational status of equipment and quantify product quality. By connecting sensors and devices to the network, organizations can analyze this crucial data in real-time.
According to the Ministry of Economy, Trade and Industry’s 2022 Monodzukuri White Paper, 67.2% of companies answered that they are using digital technology in their manufacturing processes and activities.
An increasing number of companies are shifting to production activities that do not rely on intuition and experience, but instead collect various data in real-time and visualize the status of products and equipment.
Reference: 2022 White Paper on Manufacturing | Ministry of Economy, Trade and Industry (PDF)
Why data utilization is gaining attention in the manufacturing industry
One of the reasons why data utilization is gaining attention in the manufacturing industry is the evolution of digital technologies such as IoT (Internet of Things) and AI (artificial intelligence). This evolution makes it possible for companies to find valuable information from the large amount of data being processed. Data is now a crucial resource for solving challenges.
Companies using digital technology have found:
- Improved productivity
- Reduction of workload and improvement of facility operating rate
- Reduction of lead time for development, manufacturing, etc.
- Efficient inventory management
- Improved quality
- Stable production system
Because of the above, data utilization is considered an effective way to improve operational efficiencies and productivity in the manufacturing industry.
Four challenges and solutions related to data utilization
According to the “Survey on Issues in Japan’s Manufacturing Industry and the Direction of Responses” released by the Ministry of Economy, Trade and Industry in March 2022, about 40% of companies collecting data said, “There is not much progress in data utilization. No.”
Why hasn’t progress been made in data utilization? Let’s look at four common challenges and solutions when using data at manufacturing sites.
1.Gap between management and the manufacturing floor
It’s important to introduce data utilization at manufacturing sites and measure the small improvements. In many cases, management expects there will be a significant impact on company activities immediately, which is not always the case. As a result, there is a gap between the expectations from management teams and the actual results. This leads to leaders thinking that the introduction of digital technology to manufacturing sites is not a great contribution to company results.
For management to understand, it’s necessary to promote digitization from a long-term perspective. It’s also crucial to emphasize that the data collected from the entire manufacturing site helps leaders visualize processes to help with future decision making.
2.Data siloes for each manufacturing process
In many cases, there are people assigned and responsible for managing different processes at a manufacturing site. As a result, data collection devices and networks are only optimized for each individual process creating siloes as the data captured from different processes are not linked.
To improve the production line, it’s necessary to organize and link the manufacturing data collected in each process. However, as the devices and networks used in production facilities have different communication standards, it is not realistic to standardize them with the same specifications.
One solution is to introduce a communication system that connects a programmable logic controller (PLC) that controls a programmable logic circuit and a server. By connecting devices that support various communication standards to the PLC, and by using software that enables connection settings without code, centralized data management can be easily achieved without remodeling production equipment.
3.Quality of data output from the controller
Although controllers have a long lifespan, some cannot connect to the internet, or the data format cannot be used as is. Therefore, it’s necessary to install a device that can acquire digital data and convert that data to be used with IT technology.
For example, if you are using an analog instrument, you can either replace it with a digital one, or take a picture of the instrument with a camera and output the information – read by OCR (Optical Character Recognition) – as digital data.
To acquire digital data that can be used in IT, organizations need a device that collects and outputs digital data as an add-on. In addition, a network connection is required to collect and analyze data in real time.
There is a concern that connecting a large number of devices to the network will slow down the communication speed. For this reason, Edge Computing is gaining attention as a useful method to collect data and perform primary processing to reduce the load on the network.
4.Lack of human resources who can utilize data
According to the White Paper on Manufacturing 2022, about 88% of companies feel that there is a shortage of IT human resources. With the declining birthrate and aging population, there is a shortage of human resources in every industry, and it will become difficult to hire highly skilled IT employees in the manufacturing industry. Therefore, it is necessary to have non-IT personnel in the company acquire IT skills.
Currently, there are tools that create business applications without code. If you have computer operation skills and a desire to work on business improvement, users can develop a system that utilizes data after acquiring the skills. An application written by an employee who is familiar with internal operations is more likely to be a field-ready system than an outside vendor.
Even if no-code tools reach their limits, we have experience in the system development process, so we can smoothly proceed with requests to external contractors.
5 Benefits of Data Utilization in the Manufacturing Industry
So, what are the benefits of using data in the manufacturing industry?
The use of data improves productivity at manufacturing sites. This is because the status of equipment, which until now relied on intuition and experience, can now be visualized in numbers, allowing operations to proceed based on data-based decisions. If you can visualize the production line from the operation data of each piece of equipment, you can see which equipment needs to be improved based on operation rates.
As organizations focus on measures to improve productivity, employees will immediately feel the effects, which will also lead to an increase in employee motivation.
2.Verbalization of know-how
By making full use of digital technology, organizations can standardize the know-how of experts. Some companies are even achieving automation.
With the evolution of sensors and IoT, it is now possible to acquire real-time data on the senses of craftsmen and the environment inside equipment. By linking a wide variety of acquired data with the quality of finished products, it is possible to verbalize the know-how of experts in detail.
Even if a skilled worker retires, the company can maintain its competitiveness because it can reproduce high technical capabilities based on data.
Another advantage of using data is the ability to reduce production activity losses.
By monitoring and visualizing production line losses in real-time, manufacturers can quickly catch abnormalities in equipment. Even the small anomalies that are often overlooked can be caught early thanks to aggregated data. Equipment can still run as an abnormality occurs, reducing product loss.
Users can also analyze the cause of defective products by analyzing the data.
4.Quality improvement of production line
By linking the data of each process, manufacturers strengthen the traceability – from the input of raw materials to the inspection process – improving the quality of the production line.
If organizations link the manufacturing conditions of all parts, manufacturers can then compare the data of defective products found in the inspection process and normal products, identifying the cause of defects.
In addition, by analyzing the relationship between processing conditions and quality and finding trends and patterns, manufacturers can accurately communicate product improvement points to the design department. Data utilization can also be used to improve the quality of production lines.
5.Increase added value
By analyzing operation data after the product is sold and implementing positive changes in product design and process design, manufacturers can improve added value.
For example, some companies remotely analyze the customer’s operation status and usage environment and then propose optimal operation suggestions to add value in the form of power saving.
By utilizing the data obtained from the sensors attached to the product and providing an unprecedented level of customer experience, the value of the company’s products is improved.
Leveraging Edge Computing to Utilize Manufacturing Site Data
An increasing number of companies are leveraging critical manufacturing site data to improve the productivity and quality of manufacturing processes.
To generate the data necessary to solve the problem, efforts such as installing new sensors and digitizing analog data are necessary. In addition, to use data to improve operations, it is crucial to collect and analyze data from sensors and devices scattered throughout the production line.
However, sending this huge amount of data from the production line to the cloud server for processing puts a heavy load on the network. For this reason, the introduction of Edge Computing, which performs primary processing closer to the site where data is generated, has been attracting attention in recent years.
Edge Computing platforms, which are key to such manufacturing sites, are high performance, reliable, and secure. They must be easy to service so that those who are not familiar with IT can still operate them easily.
Please refer to this article for more information on Edge Computing for data utilization at manufacturing sites.
Availability in Edge Computing | Stratus Blog