Real-time Monitoring, Analysis and Predictive Maintenance of Industrial Machinery based on industry 4.0 concept using IoTs

Project Title

Real-time Monitoring, Analysis and Predictive Maintenance of Industrial Machinery based on industry 4.0 concept using IoTs

Project Area of Specialization Internet of ThingsProject Summary

The advancement and rise in complexity of machines due to the continuous increase in demand for usage and volume has led to several bottlenecks that inhibit the devices’ full potential so, the need of the hour is to transform Industry 1.0 to Industry 4.0 which is all about connectivity. Let’s get familiar with all the industrial revolutions. We have a total of 4 revolutions till today.

• Industry 1.0 (a machine-driven mechanization) Machines were driven initially by steam engine and motors.
• Industry 2.0 (assembly line production) A large-scale manufacturing was done using assembly line technique.
• Industry 3.0 (a step towards Automation) A step towards automation made the ides of partial-automation possible using memory-programmable controllers, PLCs and robots.
• Industry 4.0 (an IOT sensor-based system)Automation and data exchange paradigm creating reprogrammable machines using IoT sensors and machine learning thus making a new concept of active supervision.

Our vision goal for this project is to contribute towards Industry 4.0 through digitization of machines. The solution that the project aims to provide is the real-time monitoring and analysis of the digitally interconnected IOT nodes using mesh networking. Use of Arduino with sensors will be made to detect the flow of current, temperature of environment, vibration, and then these detected values will be move to Cloud for storage thus monitoring the working of all the machines and devices allowing the factory to work efficiently. Predictive maintenance will be done on the basis of drawn current and vibrations of the machine, crossing a particular threshold (alarming the user that there is some trouble in the object under consideration). An application on mobile phones will make it more proficient and well-organized for the user to check the behavior of machine anytime and creating a sense of smart factory that can be accessed anywhere. Major features of the project include mesh networking, automation, efficiency of data collection, detailed record for the user.

Project Objectives

With the ascent of industry 4.0 concept and the rise of industrial IoTs and other technologies used for industrial automation has started a push towards smart factories. Our aims and objectives include:

• Reduce the need for active supervision to solve basic issues
• Make a check of the working hours of the machines(equipment)
• Predict and analyze of machine’s behavior
• Design of IoT nodes for data collection purpose.
• Communication with mesh networking
• Pushing data on cloud to store
• Develop app to monitor data of machines
• Utilize machine learning and AI for predictive maintenance

In order to achieve the objectives mentioned above, the algorithms will be tested and implemented on both software and hardware.

Project Implementation Method

The technology we are going to use is divided into two parts. First is the hardware which includes an IoT node. This node will consist of a current, temperature and a vibration sensor – for measuring the current consumption, temperature and vibrations of the machine caused by the working of machine. This node is an ESP32 based Arduino and we will create a mesh network to collect the data of multiple machines on the floor and to make them able to communicate with each other. All this data will be used to monitor the normal behavior of the machines and to develop a machine learning algorithm which could detect any abrupt changes in the behavior of the machine. This node will transmit all the collected data to a cloud server at regular intervals. For cloud we are using Firebase database. The second part is the software part. This includes the modeling of data structure in the cloud in order to keep a track of different machines and to provide the data to only a specific person. Then we will create a mobile application, which will collect all the data from the cloud and displays it in real time. Application user will be able to monitor the state of the machine, whether it is working or not. The user will also be able to check the total working hours of the machine in past. We will use C language for Arduino programming and Kotlin for android application as this is the official language declared by google.

Here is a small system level diagram:

Benefits of the Project

As stated in the project’s summary, it’s all about connectivity, it’s all about making the machines to reconfigure themselves by appropriate methods. Our project has the following incredible benefits:

• It will reduce the need for active supervision to solve basic issues.
• It will make a check of the working hours of the machines(equipment) and real monitoring will be done.
• Prediction and analysis of machine’s behavior will make the owner up-to-date about what is happening with the object.
• Our project will contribute towards Industry 4.0 vision by increasing the efficiency and saving a lot of money and time as well.
• App will be able to make the owner check the working and state of any machine (those with the IOT nodes) anywhere and anytime.
• Cloud storage will contribute towards the data record in real time processing.

Technical Details of Final Deliverable

The final deliverable will consist of a hardware node and a mobile application. The hardware node will consist of a current, temperature and vibration sensor. Each node will be connected to a single machine and will collect its data based on the working of machine. These nodes will also be able to communicate with other machines in the network for better performance. All this data will be uploaded to a database - most preferably Firebase - in real-time. This data will be used by a machine learning algorithm for both learning and predicting the normal behavior of the machine. If there is any abnormal value among data at any time the user will be notified instantly. Finally, the mobile application will display the data in real-time and will also allow the user to interact with the machine. The application will be designed in such a way that each machine operator will be able to receive all the data of only the machine he is working on. While the data of all the machine in a plant will be available to the manager of the plant. The application will push notifications in real-time based on the output of machine learning algorithm if there is any abnormality among the data received by the node.

Final Deliverable of the Project HW/SW integrated systemCore Industry ManufacturingOther Industries Others Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI), Cloud InfrastructureSustainable Development Goals Decent Work and Economic Growth, Industry, Innovation and Infrastructure, Responsible Consumption and ProductionRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	14180
Node MCU	Equipment	6	900	5400
Current sensor	Equipment	6	800	4800
Vibration sensor	Equipment	6	300	1800
Temperature sensor	Equipment	6	130	780
Pcb board	Equipment	6	150	900
Passive components	Equipment	1	500	500