Industry 4.0

Industry 4.0 represents the future of industrial innovation, also being called „smart factory”. Through the use of cyber-physical monitoring systems a company can obtain a virtual copy of the psysical on which to apply decentralized decisions. All the systems interconnect and comunicate with each others and with humans in real time.

The access to the Internet has grown from an estimated 10 million people in 1993, to almost 40 million in 1995, to 670 million in 2002, and to 2.7 billion in 2013. The Internet has started to be used so much in industry, that a consortium has been founded, called Industrial Internet Consortium, which covers energy, healthcare, manufacturing, public sector and transportation (online at According to the Industrial Internet Insights Report for 2015 80% to 90% of the surveyed companies indicated that bug data analytic is in the top three priorities.

There are four design principles in Industry 4.0. These principles support companies in identifying and implementing Industry 4.0 scenarios.

Interoperability: The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) or the Internet of People (IoP).

Information transparency: The ability of information systems to create a virtual copy of the physical world by enriching digital plant models with sensor data. This requires the aggregation of raw sensor data to higher-value context information.

Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensibly for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.

Decentralized decisions: The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomous as possible. Only in case of exceptions, interferences, or conflicting goals, tasks are delegated to a higher level.

Business applications

#1 (Defrost refrigerators). The defrost refrigerators are professional equipment which raise up their indoor temperature with 2⁰C periodically. If the door is opened when they are defrosting, the temperatures raises uncontrollably and they get broken. Therefore HOLISUN developed a data mining tool for analyzing the behavior of the user and predicting the next period when defrosting an start .

#2 (Predictive maintenance). For companies using large machines (such as production lines), the maintenance costs are normally a major portion of the total operating costs in most plants. On the other hand, the downtimes due to faults of the machines affect up to 30% of the profit. Therefore collecting the dat afrom those machines, mining it and predicting the next fault is crucial and can reduce the maintenance costs up to 50%. HOLISUN did it for the most important producer of shoe production lines in the world .

#3 (Agriculture 4.0). According to Climate-KIC, the agriculture as is now could not support the population of the Earth by 2030. Therefore an intelligent agriculture is emerging, based on Internet of Things. A major priority is the intelligent crops production, which requires a thorough surveillance of the agri climate (e.g. earth moisture and temperature), their accurate prediction and intervention when the value risk to become abnormal. HOLISUN is able to collect data from the crop fields, predict the tomorrow’s values and alert the owner if needed.


  • Analysis and prediction of the user’s behaviour
  • Analysis and prediction of the provider’s behaviour
  • Predictive maintenance
  • Fault analysis and prediction
  • Factory of the Future (FoF)

For more details see:

Industrial Internet Insights Report For 2015

The Basics of Predictive / Preventive Maintenance

Applying data mining in the context of Industrial Internet.