KMEW's Dream of Automatic Manufacturing of Lightweight and High-quality Roofing Materials Comes True with DX

Executive Summary

KMEW, established by Kubota Corporation and Panasonic Holdings, is a leading manufacturer of roof tiles, exterior wall panels, and rain gutters. KMEW’s light and beautiful roof tiles and exterior wall panels are well suited for use in Japan, where earthquakes and other natural disasters are a frequent occurrence. KMEW holds the top share in Japan’s roofing material market.

The Shiga plant, one of KMEW’s principal production facilities, manufactures fiber cement slate tiles for customers in western Japan. The Shiga plant has been working with the company’s Nara Techno Center to improve product quality. Based on an analysis of manufacturing data collected over long periods of time, KMEW sought to identify factors that affect product quality, but it was difficult to reach a conclusion due to fluctuations that occurred during the manufacturing processes. Therefore, KMEW approached Yokogawa and decided to work together with them to analyze data and build an automation system. As a result of their collaboration, an automatic control system was introduced to correct factors in the tile molding process that were affecting product quality. This system eliminates the need for human intervention and enables KMEW to produce consistently high-quality tiles without human intervention.

 

The Challenges and the Solutions

The slate tile manufacturing process

The manufacturing process is automated by a programmable logic controller (PLC). The slate tiles are manufactured by mixing raw materials (cement, pulp, water, etc.), spraying the mixture onto a conveyor belt, and molding it with rollers. The picker roll used to scrape the slate material and flatten it to a specified thickness is a key determinant of product quality. The scrapings are returned to and reused in the manufacturing process.

PLC-controlled production line

Picker roll

Overview of the slate tile molding process

 

Factors that make data analysis difficult

Since 2002, the Shiga Plant has collected 26 million points of data per day on its manufacturing facilities and processes. This data can be viewed using a program developed by Yoshiharu Nakata of the company’s Nara Techno Center. Members of an on-site capability reinforcement team have analyzed this data to pinpoint abnormalities that cause variations in quality, but this has been difficult for the following reasons:

• Raw materials are imported from various sources and vary in quality year in and year out.
• The moisture level in the returned material varies depending on where it is generated in the process and how much time has elapsed.
• In response to the above-mentioned variations, experienced operators frequently make adjustments to the height of the picker roll, the amount of water that is added, and other items based on their know-how.
• The range of data from the entire facility is too great to analyze fully.

The molding process, from the weighing of raw materials to the forming of the slate tiles, takes one to two hours. Moreover, the entire manufacturing process takes two days. While quality defects can certainly be detected at the end of this process, a large number of defective products will be produced during that time. To avoid this, veteran operators frequently change the settings of the manufacturing equipment based on their own experience while observing the manufacturing conditions, resulting in a very high workload.

Even though KMEW understood from its data analysis that fluctuations in the characteristics of the materials were having an impact on product quality, it was difficult to capture data on these fluctuations in real-time. To make the necessary improvements, KMEW chose to partner with Yokogawa.

Slate tiles on the conveyor belt

 

Visualizing the characteristics of materials in real-time

In April 2017, KMEW and Yokogawa launched a kaizen workshop to improve data utilization. Toru Yamamoto, a kaizen consultant from Yokogawa, analyzed data provided by KMEW in advance and offered that the quality of virgin raw materials could be detected in real time. Mr. Yamamoto subsequently met with KNEW personnel to learn more about KMEW’s manufacturing facilities and processes, including installed sensors and their locations. He also consulted operation logbooks and had the plant operators fill out questionnaires. Using this information, KNEW and Yokogawa proceeded with further analysis to identify a logical means for evaluating fluctuations in virgin materials. Discussions on data-related matters were always heated, and Mr. Yamamoto always left the Shiga plant after dark.

As a result of an analysis of approximately 120 tags, they identified several tags that were correlated with fluctuations in raw material characteristics. In December 2017, they completed the construction of a material condition visualization system that was capable of monitoring fluctuation patterns in raw materials, enabling the correct operation of equipment based on the condition of the raw materials. With this achievement, the workshop was successfully concluded.

 

Automatic control system for picker roll

As a next step, in 2020 KMEW and Yokogawa took on the challenge of automating the height adjustment of the picker roll. Two young workers, Toshiaki Fujisawa of the Nara Techno Center and Fuyuki Ideno of Yokogawa, joined the project, and data was analyzed to define the operating conditions for the automation system. An additional objective for KMEW was to arrange and make use of all the know-how of the people involved in manufacturing, especially the know-how that Koichi Tanaka, the operations manager, had accumulated.

For this data analysis, KMEW relied on Yokogawa’s Process Data Analytics (PDA) software, and their personnel received instruction on how to use this tool from Yokogawa. In so doing, they acquired data analysis capabilities that could be put to use even after the project came to an end. KMEW and Yokogawa discussed the results of their data analysis many times while sharing knowledge with each other.

Next, KMEW and Yokogawa worked to study the control sequence and build an automation system that automatically adjusts the height of the picker roll based on data on items that impact product quality.

Location of the picker roll

Features of the automation system:

• Utilizes Yokogawa’s Exapilot operation efficiency improvement package
• Exapilot determines the proper height of the picker roll in real time based on data such as the length, weight, and thickness of the slate, and associated data.
• Setting values are sent to the PLC via an OPC server.
• The PLC issues commands to control the height of the picker roll.

Thanks to the automation system, the Shiga plant is now able without manual intervention to produce slate tiles with consistent quality. Operator workload is dramatically reduced, and operators are able to devote more of their time to higher-level quality control tasks.

Monitoring screens of the picker roll automation system

 

Customer Satisfaction

-- Why did you contact Yokogawa?
“As one of KMEWS’s leading manufacturing facilities, we already had experience in gathering, visualizing, and analyzing plant data to eliminate variations in product quality and reduce operator workload. Moreover, we aimed not only to introduce feedback control but also to introduce feedforward control by estimating quality values from data such as the state of raw materials.”

“We had grasped most of the factors that affect product quality, but frequent manual interventions added noise to the data and kept us from reaching final conclusions. So we decided to team up with data analysis experts and contacted Yokogawa.”

“As we had had no contact with Yokogawa up till then, we first approached them by visiting their booth at a trade show.”

Airplane icons inspired by the autopilot system
point to status messages on operating conditions

-- What did you think of Yokogawa’s problem-solving approach?
“I think Yokogawa’s approach of striving to acquire a complete understanding of a manufacturing process, jointly analyzing data with a customer, and listening to and also sharing its own views with the customer, was suitable for us. In our industry, even if we try to manufacture under the same equipment conditions, it is difficult to ensure a stable outcome due to inevitable variations in the condition of the raw materials and equipment. Yokogawa thoroughly analyzed the data to understand the manufacturing processes and various phenomena that could occur. Other companies simply analyzed data, and the analysis results did not correspond to fluctuations in the plant conditions.”

“Yokogawa listened carefully to us as we shared our knowledge and showed us various possible cases along with numeric data, so everyone working on this project was satisfied.”

“I was also convinced.”

“I wanted to extract all of Mr. Tanaka’s know-how and organize that, and my wish came true.”
 

-- How frequently were operators having to make adjustments?
“In addition to adjusting the height of the picker roll, the operators were having to adjust the pressure that was being applied at different points, alter how much water was being added, and so on. Those tasks increased their workload.”

“Veteran operators have their own skill sets, and this was making data analysis more difficult because each operator was taking different actions. But now, operators are looking at the data and sharing information about product properties. In many cases, the data supports what they perceive to be correct.”
 

-- What’s the benefit of implementing the automation system?
“Except for the first five minutes after the start of production, when data is being acquired, operation is automated. Operators monitor the monitoring screens and manually intervene if there is a deviation in the automatic operation, but such manual interventions are rare.”

“Instead of just having to visually monitor the production line, operators can focus on quality control work. Given that the working population is declining, it is very important for people to have work that motivates them. Taking advantage of the reduction in workload made possible by the automation system, I want our young employees to be able to take on new challenges.”

“I first thought about automating the height adjustment of the picker roll 20 years ago. I thought we should break away from manufacturing that depends on individual skills, but we lacked the data to do that. Thanks to this project, my dream has finally come true.”

“Through this project, I feel that I have achieved what I wanted to do. I think successful experiences like this can be motivating factor. I’d like to spread this kind of experience throughout our company.”
 

-- What challenges do you want to take on next?
“We want to improve data quality, accuracy, and reliability. If the weight of the slate tiles can be reduced while maintaining their strength within an acceptable product quality range, this will reduce costs.”

“Lightweight roofing materials are said to make buildings more earthquake resistant. Japan is a country with many earthquakes, so in order to improve life here, we definitely want to achieve further weight reductions with our slate tiles.”

“My next challenge is to extend what has been accomplished at the Shiga plant to all of KMEW’s plants. To do that, we must increase the number of people who can master data analysis.”

“Environmentally-friendly and carbon-neutral manufacturing will be required in the future. It may be necessary to change raw materials and manufacturing methods. We will continue to use our data and our knowledge to tackle various challenges.”
 

-- What are your expectations for Yokogawa?
“We would appreciate Yokogawa’s continued support with automated control. We have to expand our activities to other manufacturing processes and other plants. What we are aiming for is feedforward control.”

“Our manufacturing sites will be stronger if plant staff and leaders have more time for more value-added tasks. I would like to ask for Yokogawa’s continued cooperation with these activities and for their assistance in training human resources in the analysis of data.”

(From left) Mr. Kamikawa, Mr. Tanifuji (Shiga plant), Mr. Nakata, Mr. Nishiura (Nara Techno Center), Mr. Tanaka (Shiga plant),
Mr. Fujisawa (Nara Techno Center), Mr. Ideno, Mr. Yamamoto, Mr. Miyagawa, Mr. Yamaguchi (Yokogawa)

 

Department name and job titles are as of interview.