Author: Nino Published: 2023-3-17 09:04 

Automation has grown significantly from the pandemic to the present, with the global industrial automation market size estimated at USD 196.6 billion in 2021 and expanding to over USD 412.8 billion by 2030, and is expected to grow at a compound annual growth rate (CAGR) of 8.59% during the forecast period from 2022 to 2030.

At the same time, real-time data analytics has grown significantly with the increase in data volume, the increased consumer acceptance of the use of their behavioral data, and the rising demand for predictive maintenance in industrial automation. Manufacturing and other industries are investing in related technologies and equipment, while the Asia-Pacific region has a significant market share in the global industrial automation market, and some research institutions expect the region to maintain its market dominance. The reason for this is the economic growth of emerging countries such as India and Indonesia, which has led to an increase in the number of applications year by year.

Figure 1: Industrial transformation has led to rapid growth in the global automation market. （source：Precedence Research）
In addition, the improvement of enterprises' mastery of smart devices has made the application of industrial automation monitoring technology more frequent, and enterprises can grasp variables such as temperature, current, voltage, speed, and vibration in real time at any time.

Industrial robots, computer vision systems, human-machine interfaces, sensors, 3D printing, industrial computers and other software and hardware are rapidly merging under the massive transformation needs of the industry, which has made related players, such as ABB, Emerson Electric Company, Fanuc, General Electric, Honeywell, Mitsubishi Electric, Rockwell, Schneider Electric, Siemens, Yokogawa Electric, and Omron Corporation, become the biggest beneficiaries.

Cloud providers have become an important driver of enterprise automation

Generally speaking, the way of transformation of the manufacturing industry: from large enterprises to small and medium-sized enterprises, from advanced manufacturing to traditional manufacturing fermentation. In a narrow sense, the automation industry does not include cloud operators, but at present, a lot of data can be processed and analyzed on the cloud, and many automation companies such as Siemens, ABB, etc. have also begun to cooperate with large cloud enterprises, and customers of cloud enterprises can also benefit from large automation enterprises. Among them, AWS, Microsoft, Google, and IBM are the four companies that account for more than 50% of the global cloud market, and these four companies continue to innovate based on cloud vertical solutions, providing integrated services from IaaS, PaaS to SaaS, and embedding automation solutions to expand their service scope.

The reason why the cloud plays an important role in the automation transformation is that it can provide a complete IT computing platform for enterprises, and under the pay-as-you-go model, enterprises can obtain a variety of complete services without spending too much IT maintenance budget, greatly reducing the cost of maintaining databases, and focusing their limited manpower on other high value-added activities. The second is the ability to flexibly adjust, as enterprises grow, the amount of data accumulated will gradually overwhelm the original use space, and by changing the type of cloud services, enterprises can choose from different types or capacities of hosting solutions, increasing the agility of enterprise IT. Finally, due to the change in interaction mode and the reduction of physical activities, enterprises will accelerate their transformation, and the types of data will grow rapidly, and the data type will change from text to text and image files, hyperlinks, etc., how to integrate and analyze multiple data, and apply it to operational insights.

Figure 2: Honeywell integrates its solution into the AWS cloud. （source：Honeywell Cloud SCADA）
The aforementioned cloud operators offer a more integrated solution. In the more niche market, it is provided by major automation manufacturers, such as Honeywell, which integrates its own hardware and AWS software, provides services such as digital meristem, MES, IIoT platform, drone fleet, etc., and customizes it for specific sub-industries, such as electronics manufacturing, chemical energy, aerospace, and self-driving car industry. These automation companies themselves have rich experience in transformation, and their grasp of domain know-how is relatively complete, and the cooperation with cloud enterprises has quite a comprehensive effect, and it is expected that more large automation companies will cooperate with these cloud companies in the future, and the trend of Evergrande will be more obvious.

ABB is digitally transforming from the lowest layer

Originated in Switzerland, specializing in automation and intelligent manufacturing, ABB is famous for its robot products, and is now one of the world's four leading robot companies, along with KUKA (KUKA) in Germany, Fanuc (FANUC) in Japan, and Yaskawa Electric (Yaskawa).

Although the Lean Six Standard Deviation method has allowed ABB to operate effectively for decades, it is still a little insufficient in the wave of digital economy, due to the large scale of the business body, the information flow of multiple factories and finishing supply chains in different regions often delays and incomplete information, so it is necessary to explore the process from the bottom. The company's vision for transformation is clear: to make the process transparent, so that it can move from identifying problems to predicting them, and the integration of process data at all ends will help the group to have a single-truth interpretation.

Figure 3: ABB partnered with Celonis to explore internal processes. （source：ABB）

ABB has two approaches. First, due to the large value chain of the group, it is most efficient to have front-line employees in the operation department and the quality department directly analyze the differences in each process node. Since data is not valuable on its own, and most IT professionals focus on "system, network, and database management", it is difficult to rely on traditional information management systems (MIS) and network management manpower to gain insights and find problems from huge amounts of data, so it is time to find an external collaboration partner after combing through all kinds of data.

Second, since ABB's current digital tools were not enough to support the huge process exploration, the company turned to external solution providers to support, and after several evaluations, ABB chose to cooperate with Celonis, a German data processing company, which is best at business process mining technology, extracting data from the company's individual events for algorithm analysis, in addition to ABB, its customers are Siemens, 3M, BMW, Leyard, General Motors, etc., the company is currently valued at $10 billion and has already joined the ranks of unicorns. ABB has successfully broken down data silos with Celonis' process mining technology, integrating global financial data and optimizing it for different business processes (orders, purchases, payments).

Smart logistics and warehousing will be one of the key growth markets in 2023

At present, the establishment of a digital supply chain has been an active strategy for the global manufacturing management class, hoping that in the face of the impact of major emergencies, enterprises can flexibly respond to the impact through rapid resource integration and cooperation between upstream, midstream and downstream partners in the supply chain, so that enterprises can quickly turn to other alternatives in a short period of time, such as moving production bases or finding alternative markets, so as to minimize the risks caused by emergencies and even quickly restore the original operating state.

In the process of building a resilient supply chain, "backup capability" is even more important, the so-called backup capability refers to the real-time response mechanism, enterprises can independently disperse production, deploy warehousing bases or find other alternative sources in advance in the event of shocks, and can quickly plan the second and third alternative production bases, and integrate logistics, people flow, information flow, cash flow and other projects through intelligent systems to improve prediction and response capabilities. Under the condition of redundancy capability, enterprises should respond to risks as quickly as possible, such as establishing a supply chain information connection mechanism, once a risk occurs, it can grasp the risk in the shortest time through information sharing, and at the same time activate relevant risk avoidance measures.

At the same time, for supply chain managers, an aging workforce and a declining workforce are also one of the main reasons for companies to invest in warehouse automation. In terms of geographical distribution of the market, benefiting from the huge demographic dividend, the OEM industry cluster and the vigorous development of e-commerce, Asia has become the fastest growing region in the world for smart warehousing. Electronics manufacturing, automobile manufacturing, consumer products and other international manufacturers have set up a large number of factories and warehousing centers in Asia, and before the pandemic, the original "Made in Asia for the world" has gradually changed to "Made in Asia for the Asian market". Coupled with the varying levels of digital infrastructure in different countries, companies seeking to establish regional manufacturing hubs may face data transfer speed delays, differing network standards, local vendor competition, and regulatory hurdles. Therefore, local manufacturing is the protagonist of smart factories, but to supply the market locally, the deployment of smart warehousing is a key element for enterprises to invest in supply chain transformation and local manufacturing.

Figure 4: Haier's automation transformation covers everything from factory to logistics. （source：HBS Digital Initiative）

After the Sino-US trade conflict and the impact of the epidemic, the company changed its global supply chain strategy from a long chain to a mixed chain type, and the North American market was supplied by the US factory (regional manufacturing center), and its nine factories in the United States have invested US$700 million in smart warehousing in the past few years, introducing a large number of unmanned guided vehicles (AGVs), autonomous mobile robots (AMRs) and other equipment to replace excessive labor costs and apply them to important processes such as picking, packaging, and shipping.

Coincidentally, Sweden's IKEA has many smart warehouses around the world, including a large number of smart conveyor belts and autonomous mobile robots, and recently deployed drones to scan two-digit codes and count goods. In addition, because intelligent warehousing generates a large amount of data, it is also a common practice in the industry to add algorithm tools for analysis and forecasting, including Dell, HP and other large manufacturers in intelligent warehousing to make good use of algorithms for inventory forecasting and capacity adjustment. The reason why these companies invest a lot of resources is nothing more than to meet the needs of local manufacturing and local supply markets.

epilogue

Regardless of whether the industry has to cope with the impact of digitalization, the transformation of business models, or even the response to extreme weather in the future, automation technology is indispensable, and in the situation of increasing data throughput, enterprises must prepare their operational processes to use data to solve larger issues or external challenges in the future, which is why Thomas Devonport emphasized that enterprises should "from the inside out" The importance of improving operational processes also calls for the fact that many enterprises have a high chance of turning into a platform-based enterprise that provides digital products and consulting services in the future: good internal processes can only have the capital to carry out various innovations in the data economy, and even become the cornerstone of inter-enterprise cooperation.

Whether it is the huge virtual market brought about by the metaverse, or the quantum computer that will change the computing and analysis capabilities of enterprises, or even the climate technology/agricultural technology/food technology that is now being emphasized by OCED and the government, enterprises need to pursue smooth operation processes and lay a solid foundation for digital infrastructure in order to play more in the industrial environment of virtual and real integration.