What Is the Digital Transformation of Manufacturing?
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What Is the Digital Transformation of Manufacturing?

Why has the software industry or the hardware industry been talking about digital transformation in recent years? What is the necessity and challenges of Taiwan's manufacturing industry for digital transformation?
Published: Jun 19, 2020
What Is the Digital Transformation of Manufacturing?

Replace feelings with data

In recent years, the development of technology has become faster and faster. Big data analysis, IoT, and artificial intelligence are often dazzled, but if you think about it quietly, you will find that whether it is the software industry or the hardware industry, Doing the so-called digital transformation, but what is the purpose of pursuing digitalization?

To obtain more complete data

In the past, regardless of any industry, people who would say that old experience is very important, because they have a long experience in the workplace, and have encountered large and small things in the work, so when a problem occurs, they can respond faster and make a relatively high accuracy. Decision-making, this is impossible for a newcomer with a good education and a high IQ.

But if people with experience are asked to explain why this is the case, it is difficult for them to explain systematically and structurally. They usually say, "With my years of experience, I feel that I want to do this, and I don’t know why..." It is subjective, and because there is no objective evidence to refer to, sometimes it is easy to misunderstand when communicating with others.

Today, if the feedback of various actions in the workflow can be stored digitally, these are the best evidences, allowing everyone to objectively analyze and discuss the actual data status of each link, and reduce misunderstandings in communication, and to improve the shortage, which is why the digital transformation is being promoted regardless of industry.

Replace sensations with data and strengthen intuition with data

To take the most obvious example, there have been very big changes in the marketing industry in the past few years. In the past, no marketing expert could prove the marketing expenses spent by the company, what impact it caused and what effect it had in the past. Advertisement is like throwing a bird at random. No one knows whether it hits the target customer group, or how many orders come because of the advertisement. The company can only trust the marketing experts completely.

But in the past few years, with the advancement of network technology, e-commerce has been able to achieve precise marketing, accurately target the target customer group, and can display detailed reach rate, conversion rate...etc. This is the data analysis power.

Digital transformation and development of the hardware industry

Before delving into the digital transformation of manufacturing, let’s talk briefly about the development of IT and OT. Most people have heard that software information technology is called IT (Information Technology), and hardware equipment technology is called OT (Operation Technology) in the industry.

Early IT and OT were doing their things. Various information systems (ERP, MES, SCM, CRM... etc.), regardless of finance, accounting, customer list, production management... etc., were responsible for software engineers in the IT department, However, the on-site OT hardware equipment engineers are responsible for the various process equipment of the factory, and the information of each other is not directly connected. When the company's financial accounting system requires various manufacturing time and costs of the factory, only on-site personnel can be asked to count and enter data manually, which is relatively low in terms of timeliness and accuracy.

Software companies, especially Internet companies (Google, Facebook) have long understood the importance of data, so they have worked hard to collect behavioral data very early.

Although the hardware manufacturing industry has a slow start, it also recognizes the importance of digital transformation. Only by grasping more real manufacturing data can we reduce the error rate of manual operations, improve the accuracy of decision-making, and better achieve quality control. Even quality prediction, equipment predictive maintenance.

The concept of smart manufacturing has actually existed since the beginning of the 21st century, but it was limited by the lack of maturity of the hardware communication technology at that time, and the cost of introduction was also very high. Therefore, only the semiconductor industry that requires the most process precision is introduced first, and only They have this financial power.

By around 2015, the hardware communication technology has become more mature, the product price has dropped a lot, and the situation of device networking has become more popular. This is why the Internet of Things (IoT of Internet) has suddenly been discussed by many people. With such technical support, the concept of smart manufacturing has been erupting for a long time, and more and more manufacturing companies are actively introducing it.

From Industry 1.0 to Industry 4.0

Is smart manufacturing automation? The answer is no. Automation is only the first step of intelligence. Automation is to reduce manual operations, whether it is production, handling, or data copying. Intelligence is to summarize and analyze the collected data to improve the accuracy of decision-making. rate. The two are different, and there is still a way to go from automation to intelligence.

If smart manufacturing is divided into different stages, the current highest stage is the so-called Industry 4.0. Briefly explain the difference between industry 1.0 and 4.0:

  • Industry 1.0 is mechanization, using machinery to replace manpower and animal power to accomplish things that could not be done otherwise.
  • Industry 2.0 is automation, using various sensors and PLC controllers to allow the device to automatically mass produce the same product.
  • Industry 3.0 is informatization, and began to collect production data for statistical analysis to improve R&D efficiency and reduce production costs.
  • Industry 4.0 is intelligent. It integrates information flow, gold flow and logistics through the network, collects a larger amount of more real-time data, and the system assists in data analysis and prediction. For example, when an order comes in, the production line can immediately adjust the production schedule and shipment according to the order content, and achieve quality prediction and equipment predictive maintenance.

Most of the small and medium-sized manufacturing industries in Taiwan are still at the stage of Industry 2.0, that is, the production line equipment has certain automation capabilities and can be mass-produced, but for various types of production data, such as process data, production staff identity, and production time …Wait, not much is collected, and manual work is required, so that the data cannot be real-time, and there is also the risk of copying errors and loss.

What is smart manufacturing?

Besides, many people also asked if IT+OT is smart manufacturing?

It is true to have these two fields, but one important field is missing, that is, industrial knowledge (Domain Know-how or Data Technology, DT). Whether it is OT's automation equipment or IT information system, these are just tools. , Software and hardware integration can only collect more data more conveniently, but how to apply the analysis results to actual work, this tool cannot help.

Only customers themselves understand the needs of the industry best. Without industry knowledge, no amount of data is useless. Therefore, only by combining the three fields of DT, OT and IT can we achieve true smart manufacturing.

Introduce any new technology, the management thinking should also be adjusted

But the integration of the above three areas is only basic. Many companies still ignore one thing, that is, management thinking.

When all management systems are established at the beginning, they must develop the most suitable management model under the existing constraints. When the company introduces new technology tools, it breaks through some of the original restrictions, such as communication methods, collaboration methods, etc., but if it still uses the old management model and system, it is still tied to the old restrictions.

Therefore, digital transformation is not about buying software or installing hardware. The most difficult and time-consuming is actually to adjust the company's existing management thinking and models.

Just like any company is going to import ERP is a big deal, because not only is the system installed, the entire company's work flow and management system must be adjusted, and the usage habits must also be changed. This is a process that is necessary for the introduction of any new technology. Smart manufacturing is also needed.

The needs of Taiwan's manufacturing customers

Although Industry 4.0 looks the most powerful does every factory need to achieve Industry 4.0? I don’t think so.

The characteristics of some industries do not require too precise control. From the perspective of business thinking, if the value collected by sophisticated data for customers is not in line with the investment cost compared to the investment costs that customers have to pay there is no need to do it.

For the small and medium-sized business customers I met, the most needed at present is to upgrade from Industry 2.0 to Industry 3.0, that is, to introduce paperless electronic newspaper or electronic production resume, the system can automatically record each order is Who did it, the actual production quantity and operating time... etc., and integrated various ERP and MES information systems, so that no matter the production management, quality control, warehouse can quickly obtain production data, greatly improve work efficiency, but not yet Need to do so-called big data analysis and prediction.

Of course, some large customers want to do data analysis, quality prediction, and equipment prediction and maintenance, but this will require customers to invest more capital and time before they can achieve the method. The relevant IoT infrastructure must be completer and more collected enough data, so that the results of the analysis will be more accurate, definitely not in the short term.

In the field of smart manufacturing, there is no best solution, only the most suitable solution. According to the actual needs of different customers, to help tailor a most suitable plan to bring customers the greatest return on investment.

Published by Jun 19, 2020 Source :bizthinking

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