Manufacturing 4.0: Design of Smart Manufacturing Systems


Predictive maintenance(PdM) is a strategy which utilizes predictive tools to contentiously monitor the state of machine components or process in order to determine when maintenance actions are required. Maintenance actions are taken only when needed. Predictive maintenance has the capacity to both minimize maintenance costs and maximize the device's useful life.

Even though the advantages of PdM have been widely realized, there are several barriers impeding PdM implementation in actual practice. One main barrier is that the return on investment of PdM implementation is still unclear to both researchers and industries. Return on investment (ROI) is crucial to enterprises because most aim to make profits. Before investing in any project or technology, the enterprise must carefully study the return on investment. An unreasonable investment could be even fatal to a company. PdM requires significant investment in technique, infrastructure, training, and consulting.

In contrast, the costs and benefits of PdM implementations are often not clearly defined and evaluated in practice. The unclarity of these costs and benefits depends on the type and innovativeness of the applied technique, while in practice, the different techniques are often considered as being similar. More importantly, it is hard for industries to decide on introducing PdM if its cost-efficiency cannot be justified, especially for small and medium-sized enterprises (SMEs). Moreover, there is lacking comprehensive guidance which helps organizations to understand the cost-efficiency of introducing PdM.

Jiahong Li is currently working on investigating Predictive Maintenance Return On Investment. His work mainly include three aspects. Firstly,  he will conduct methods to help enterprises to decide if they need PdM, what PdM technique to use and where to use PdM. After decided such information, enterprises can calculate the required cost for hardware for PdM implementation. Secondly, he will define the required intangible assets for PdM implementation and try to quantify the require intangible assets for PdM implementation. Last, he will investigate the possible source of income that can be generated by PdM servitization.


Jiahong Li is a PhD candidate specializing in manufacturing systems. He completed his bachelor’s degree in Material Processing And Control Engineering in China in 2015, and finished his Master’s degree in Advanced Manufacturing Systems and Technology in the University of Liverpool in 2017. Before joining the Systems Realization Lab at The University of Liverpool, he worked as a senior manager in a Fortune Global 500 company for two years.