Operational Excellence in Manufacturing through Use of Big Data Analysis IoT Solution

Executive Summary

Kuraray Engineering Co., Ltd. (KEC), a subsidiary of Kuraray Co., Ltd., is an engineering company that designs and builds plants and installs instrumentation both for its parent company and other companies. The company is a trusted provider of solutions that rely on its extensive engineering expertise and the use of the latest technologies.

 

End User’s Challenge

Aging production facilities and the loss of operational know-how through the retirement of veteran operators are pressing issues that can have a major impact on product quality and efficiency. These problems are compounded by the need to improve operations to meet ever stricter quality management requirements.

Major issues:

• Product quality varies even when there is no change in the operating conditions.
• Operations are dependent on the intuitive judgements made by highly experienced personnel.
• Trial and error efforts to improve products, quality, cost, delivery, and safety (PQCDS) produce unsatisfactory results.

 

 

The Solution - Big Data Analysis

Yokogawa provides a big data analysis IoT solution for these end users’ issues. In an analysis project, an analyst analyzes various data, including process data, and finds out root causes while thinking and discussing together with people involved in manufacturing who have various know-how and experiences. In addition, considering and implementing of practical measures is an important part of the solution. Completing the problem-solving project as a team brings two values to the end user’s workplace. Completing the problem-solving project as a team brings two values to the end user’s workplace. One is visible value like stabilizing quality, and the other is invisible value such as converting tacit knowledge into explicit knowledge, improvement of cross-department communication and problem-solving skills, etc.

Value of big data analysis

 

Method

To get to the bottom of a problem, it is not enough to just mathematically analyze the process data. Analysis must draw on the expertise of chemical engineering, take into consideration factors such as men, machines, materials, and methods (the 4Ms), incorporate knowledge about the production process (including operator know-how) and equipment, and make use of statistical techniques.
In this analysis project, Yokogawa conducted analysis by combining its analysis methodology with the knowledge of Kuraray Engineering. Kuraray Engineering prides itself on its understanding of its customer’s operations, and this is an advantage when it comes time to analyze process data and isolate the root causes of a problem. Moreover, Kuraray Engineering’s relationship of trust with its customers enables implementation of measures and establishment of PDCA cycles.

Analysis approach from various viewpoints

 

 

Case Study

High-level stabilization of product quality at a fine chemical plant

For one of its customers, Kuraray Engineering built a fine chemical plant and engineered its production control systems. Once the plant was up and running, Kuraray Engineering continued to be involved in improving its operations by introducing industrial IoT, quality stabilization, and other solutions.
Although there were no known control issues at this plant, the operators of this facility were looking for ways to strengthen their competitiveness by achieving an even higher level of stability in product quality. Based on its own examination of different vendors, Kuraray Engineering selected Yokogawa as its analysis partner based on the company’s proven track record in stabilizing production quality at various kinds of industrial plants, including in the chemical industry.

 

Working together, Kuraray Engineering and Yokogawa analyzed and organized process data using Yokogawa’s Process Data Analytics software, and examined information including the production process and the on-site know-how using various analytical techniques. In many cases, tacit knowledge, which each operator has, is not shared each other. Organizing and sharing them as explicit knowledge is useful not only for the analysis project, but also for other improvement activities. Kuraray Engineering organized customer's knowledge with the people involved in manufacturing and gave Yokogawa various thought-provoking to support Yokogawa’s analysis.
As a result, several causal factors that impact product quality were identified. Based on this, Kuraray Engineering proposed to the customer solutions such as the introduction of higher-precision sensors at important control points, the addition of new quality control points, and the modification of control sequences. These improvements have been implemented at this plant, and efforts are underway to verify the resulting improvements.

 

Message from Kuraray Engineering

Kodai Nakagawa, Engineering Division, Kuraray Engineering Co., Ltd.:

“We have been working to improve the facilities and process control at our customers’ plants. With its knowledge of the chemical industry, Yokogawa was able to contribute to this analysis project. Yokogawa and Kuraray Engineering complemented each other’s knowledge to create a synergistic effect and provide solutions that truly addressed the issues with the customer’s production process. Yokogawa always took care to give a logical explanation of its analytical procedures and report on results, so the customer was very satisfied. Also, their written reports were very carefully prepared, detailed, and easy to understand.

All of our customers have a strong interest in AI, big data, and the IoT, which have all been in the spotlight recently, but not all seem to know how to put them to good use. We want to help optimize operations at our customers’ plants by providing high value-added solutions such as process data analysis.”

 

Satoshi Kato, Director of Kuraray Engineering Co., Ltd.:

“Prior to selecting an analysis partner we talked with different vendors. Only Yokogawa demonstrated an understanding of both the process data analytical techniques and the plant facilities and processes. I think that Tomotaka Maki, the person who analyzed the process data for this project, is a valuable talent.

Based on the results of our analyses in this project, improvements have been made such as adding sensors, and these have succeeded in stabilizing operations at this customer’s plant. The next step is to analyze which measures had been most effective. By doing so, we will keep adding to our know-how on how to improve processes at our customers’ plants. As the conditions at these plants continue to change with each passing year, process data analysis is a useful tool for clarifying the situation at each plant.

We encourage our employees to adopt the latest technologies. We aim to use the know-how that we gain through our analytical projects and through plant engineering to proactively propose new and ideal plant solutions to our customers.”

 

Message from Yokogawa

Tomotaka Maki, Yokogawa engineer:

“The end user’s plant was not experiencing any control issues, so when I first heard about their requirements I thought it would be very difficult. The key to success was being able to work closely with Kuraray Engineering, which was familiar with the plant.

There are two major phases in data analysis: one is to combine theory and data to understand what is happening in a plant, and the other is to examine and then execute measures to improve its operations. To address plant issues, both are necessary. For many of its plant analysis projects, Yokogawa includes people on the analysis team who have been involved in manufacturing operations. In this project, Mr. Nakagawa played a central role on the analysis team. Thanks to his strong relationship with the end user and deep understanding of the plant processes, analysis and planning and execution of the improvement measures went well.

Although this was a difficult undertaking, Kuraray Engineering and Yokogawa capitalized on their respective strengths to optimize operations at this plant, and received high praise from the end user.”

(From left)
Mr. Uwatoko (Yokogawa), Mr. Maki (Yokogawa), Mr. Kato (KEC), Mr. Nakagawa (KEC), Mr. Harada (Yokogawa)