The fierce market competition environment promotes the high-quality development of enterprises. With the deep integration of the new generation of information technology and all walks of life, the digital transformation of production in the process industry has become a compulsory course for enterprises. The production digitization of enterprises must first start from the perspective of enterprise demand. There is no doubt that quality is the lifeblood of manufacturing enterprises, quality can not be controlled stably, and production is a waste of resources.

For the process industry, product quality, as a result of production, is inevitably highly related to the three major elements of raw material quality, equipment operating status and process methods and Settings. Among them, the process is the most decisive and the most adaptable, the process determines the production process and equipment selection, but also the adjustment of different raw materials, different equipment states, it can be said that the process is the biggest variable affecting the stability of process industrial product quality. Therefore, in summary, the process industry to carry out the digital transformation of production is rooted in the process and the quality.

Challenges and opportunities of process industry production digitization

Process industry is the basic material industry of many industries, contributing to 60% of the total industrial output value of the country. At the same time, these industries also produce a large amount of carbon dioxide in the actual production process, carbon emissions account for 78% of China’s industrial, and the urgency of digital transformation of production is extremely high. Based on the characteristics of the process industry, we summarize the following three challenges facing the digitalization of production:

Challenge 1: How to optimize and control the key indicators of natural raw materials? What about its digital process?
Challenge 2: How to collect data effectively in the face of the characteristics of multi-variable, non-linear, large lag and large output of the production process? How to help production personnel quickly identify and locate problems based on effective correlation between data?
Challenge 3: The process mechanism is complex, and some quality parameters cannot be measured online, and the production process adjustment is often based on manual experience. How to achieve accurate digital representation of the production process based on data?

However, challenges must be accompanied by opportunities: the process industry has a good foundation for automation, which allows a large number of production process data to be precipitated, creating a good data foundation for digitalization.

In addition, compared with the discrete manufacturing industry, the single product life cycle of the process industry is long, can precipitate a large number of historical data, and the potential of value mining and application based on data is huge.

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Process industry production digitization should be based on quality stability

Some people believe that the digitalization of process industry is based on improving efficiency, but for process industry, events that affect efficiency such as equipment downtime are not inherent problems of equipment failure, raw material loss is not material management and other problems, causing downtime or product degradation are usually caused by unqualified quality, and unqualified quality is due to poor process management. Therefore, we believe that the process industry to carry out digital transformation is rooted in the process, the quality, to ensure quality stability is the fundamental path to improve production efficiency, the reasons are as follows:

Quality is the basis of corporate reputation and production: in the era of we-media, product quality problems are the easiest to be found and spread quickly, which can easily affect corporate brand image and reputation. To achieve quality stability is the lifeblood of enterprise management.
The root cause of affecting raw material management, equipment and personnel efficiency is quality requirements: due to the use of natural raw materials to produce standard products, the reasons for quality instability usually include raw material components, equipment status, staff operation level and other situations. These unstable variables need to be hedged through different process Settings to achieve stable quality.
The large lag performance of the correlation and the long feedback cycle of quality control will affect the efficiency: the process conditions of continuous production have a large lag effect on the quality results, and a long time has passed when the problem is found, and it is difficult to recover the quality in a short time, the number of affected products and the loss caused are often very large.
Offline quality measurement and long quality control response cycles can affect efficiency: Another characteristic that affects quality stability is that some quality parameters are not online and have measurement cycles. In the cement industry, for example, it takes at least half an hour from material delivery to inspection results, and often a quality fluctuation event can affect production for several hours.

The stable quality of process industry is rooted in process optimization control

Product quality, as a result of production, is inevitably highly correlated with raw material quality, equipment operating status and process methods and Settings, but the three are not simply side-by-side.

Natural raw materials are often uncontrollable, and the process can be adjusted to match different raw materials. For example, in the paper industry, no supplier can provide pulp board or waste paper that meets the same quality requirements over a long period of time; Ceramic enterprises can not continuously obtain sand from the same mine that meets the requirements of the same quality index.
The running status of the equipment usually changes with the life cycle of different consumables or spare parts, and the running parameters of the equipment need to be adjusted based on process standards. The maintenance and iteration of equipment are also carried out around the change of process requirements.
The influence of process parameters on quality was first managed by the old master’s experience. In the information age, a variety of software tools are available to support precise demonstration of the impact of process parameters on quality results. Boite Technology, led by me, has been deeply engaged in the intelligent transformation and upgrading of process industry for a long time. Our large amount of practical data has proved that the influence of process parameters and quality results is determinate and measurable. The following figure shows the correlation diagram between industrial paper quality index and process parameters.