It’s time for a change for the manufacturing industry in China. On one hand, digitization is well advanced and has already revolutionized how the world runs, with no sphere of economic activity, including fast-moving consumer goods (FCMG), the media, finance, healthcare, energy, and manufacturing, remaining untouched. On the other hand, China, one of the world's fastest growing economies, found in 2015 that its growth had slowed to its lowest rate for 25 years. Many manufacturing companies that were highly profitable during China’s summer of rapid development have entered a winter of low growth or even business decline. They are urgently calling for a fuller understanding of the future of China’s economy and seeking business opportunities under the ‘new normal’.
The problems and challenges of China’s manufacturing sector have been talked about for a long time. Since 2008, overcapacity, rising labor costs and industrial restructuring and upgrading have affected its growth and structure. Meanwhile, concepts and strategies of intelligent manufacturing (including Industry 4.0, Industry IoT, Advanced Manufacturing etc.) “imported” from other countries, which might help to solve these problems, have also been a topic in China. However, even with the introduction of Made in China 2025, there is still a huge gap and a long way to go between the neat blueprint expressed by these concepts and the harsh realities of the real world of manufacturing.
Fortunately, with continuous development and exploration, some of the paths that lead to smart manufacturing and digitization have been gradually built up. There will be many paths to the goal, but predictive maintenance has been identified as one that can be put into practice. This was in evidence at the Hannover Messe this year, with quite a few showcased examples presenting user cases and their best practices.
Will predictive maintenance be a good solution for Chinese manufacturing? The answer is YES. After decades of development, China has a huge installed base of equipment. Use, maintenance and upgrade of existing equipment require continuous servicing, so the service sector has massive capacity. For a long time, China's manufacturing industry has been mainly engaged in the assembly process, the lowest value link in the whole chain of industry; but it is expected to extend to the higher-value parts of the chain, and is changing from the original, emerging, manufacturing market with many new projects to an aftermarket with manufacturing services. Here, critical asset monitoring, maintenance and machine health analysis become a more important part of business.
Predictive maintenance helps to reduce annual maintenance cost and reduce downtime cost. Today, lower-cost sensors and automated monitoring systems are in the market; and Big Data analytics is emerging, Condition monitoring, which for a long time has been in existence to support traditional maintenance, is using these developments to realize automated solutions for predictive maintenance. For large, expensive capital equipment and rotating machinery, the cost of implementing an online condition monitoring solution is easily justified. The most important benefit is an increase in revenues, which comes from maximizing uptime and efficiency of production machinery.
In China, we already see some industries starting to adopt condition monitoring for predictive maintenance and they have seen the benefits. For example, power generation providers use online condition monitoring as the basis of quality maintenance. By analyzing operating trends, integrated with a life-curve model, the status of equipment can be determined, thereby establishing the timing of maintenance and overhaul projects, to balance with economic efficiency and device availability. Also, the machine-tool industry are installing online condition monitoring system on CNC systems to diagnose faults effectively; to sound an alarm of potential failure, indicating its location and cause; and to take the faulty module offline automatically to help maintain the unmanned working environment.
Although such predictive maintenance might only make incremental improvements to manufacturing industry, it does fit nicely and easily with the new direction of suppliers no longer simply being in the business of “manufacturing”, but being engaged in “value creation”. Online condition monitoring for predictive maintenance, a technological system related to operation, maintenance and manufacturing services, can participate in the transformation of many other industries as an information portal. The most obvious effect is to reduce operating costs, improve efficiency and optimize labor; all can be seen in a short time. In the long term, more benefits will come from a hidden effect; the ability to integrate and analyze masses of data to understand the value of its own rules.