Indian Rubber Industry
India is the fourth largest consumer of natural rubber and is the third largest producer of rubber in the world. The production capacity in India is around 900,000 tons. The Rubber Industry is a key sector in the Indian economy with a turnover of around 12,000 crores per annum. If we take a close look at the Indian Rubber Industry, there are nearly 6000 companies having 30 large units, 300 medium scale, and 5600 small scale companies. The Rubber industry in India has seen a steady growth over recent years.
Emerging Business Demands
Automation is one of the quickest developing segments in the Rubber Industry. Many manufacturers are not aware of how Industry 4.0 will impact them. By 2022, 1.7 million industrial robots will be introduced into the worldwide market. The technology is enabling firms to collect much more data.What is the best possible way to utilize this data, improve measures, support quality and help increment benefit?
Advent of Industry 4.0
The first Industrial Revolution began when humans increased productivity using steam power. The second Industrial Revolution saw a phase of rapid industrialization through the widespread acceptance of gas, water, rail networks– and most importantly– electricity, which brought about assembly lines and the beginnings of mass production. The third Industrial Revolution was marked by the introduction of Information Technology. In this revolution, machines and robots began replacing humans in production work. Now, we are in the fourth Industrial Revolution, also known as Industry 4.0.
This latest revolutionary change in computing and automation has resulted in the increase of remotely connected robotics and computer systems learning machine algorithms and controlling industries with minimal human interaction.
The Industry 4.0 revolution has contributed to the creation of “clever manufacturing/ production”. As a business is driven by data, we saw the value of Industry 4.0 immediately. With Industry 4.0 emerging in the manufacturing industry in recent years, the development of Big Data & AI has become very prevalent.
There are numerous understandings of the Industry 4.0 definition. You might have heard the buzzwords Artificial Intelligence, computerized robots, and machine-to-machine learning very frequently if your company is on the path to becoming an intelligent enterprise.
It is crucial for Indian rubber manufacturers to lead the global competition by incorporating these software developments in manufacturing. By allowing the software to maintain scheduled tasks, real-time data collection, analysing the efficiency, and reporting the desired data, human errors can be avoided & manpower can be utilized efficiently.
In today’s competitive market, manufacturers including MSMEs and SMEs need to include technological advances to empower more efficient, responsive, and precise production and have better control over operations.
Challenges faced by the Rubber Industry include:
• Minimize energy losses
• Achieve high performance
• Manufacture best quality products
• Ensure Operational and Environmental Safety
• Improve operational inefficiencies
• Supply chain demands
• On-time delivery of operational demands
• Machine Breakdown time
• Quality issues
• Reduce uncertain raw material costs
• Connecting and capturing data from machines on a single platform
Data Analytics plays an important role in providing the desired solution to the industries bringing running systems online and capturing the parameters of interest from the machines. The solutions addresses the economic, ecological and social aspects of sustainable value creation for manufacturers. There is so much more productivity enhancement that can be achieved with Data Analytics & AI deployment.
Advantages of the Industry 4.0 solutions include:
• Complete Process Traceability and Transparency
• Efficient and Effective Production Management
• Track use of consumables, and direct and indirect material availability
• Completely Automated System
• Log the batch-wise production data
• Determine the mechanical properties of rubber after post-curing
• Track and reduce rejections losses
• Observing the condition and performance of vulcanization machines and other machines
• Root cause analysis from the captured data for resolving performance and quality issues
• Increase Asset Life and Overall Performance
• Improvement in Product Quality
With Industry 4.0 solution, you will get these reports:
• Daily Production
• Plan Vs Actual Production
• Rejection reports
• Temperature log and Pressure logs
• Machine Vs. cycle log
• Number of Shots i.e. no of cycles run reports
• Cycle wise upper and lower die temperature log report
• Cycle wise hydraulic pressure log report
• Cycle wise curing time log report
Modern rubber parts are normally fabricated by Injection Moulding, Compression Moulding, and Extrusion. We can track creation and financial execution progressively and naturally distinguish shortcomings.
Industrial facility uptime is a basic requirement for effective activity and no two machines in a manufacturing plant are equal. So, it is critical to screen various boundaries to guarantee that the exhibition of your resources is kept up. The effortlessness and flexibility of our framework permits you to introduce the sensors that you need to screen personal time, administrator security, and so forth.
All Industry 4.0 projects are different, but they do have much in common. One is the need to set targets like KPIs and ROI, and to measure them.
At Knowledge Lens, deep domain knowledge allows us to use data to collect insights that are actionable, delivering improvements in line utilization, production cost, quality, power usage, process traceability, automation, optimization and more. The next level of software application is AI (Artificial Intelligence), providing Predictive Maintenance, Sales Analytics, Supply Chain Analytics, Plant Digitization, Chiller Digitization, AI Powered Vision Analytics that can help select the ultimate recipe from billions of options.
Knowledge Lens is working in:
1) Industry 4.0 related technologies (Big Data, Cloud Computing, Augmented Reality),
2) Process Integration (Human-machine collaboration, Shop floor-equipment)
3) Sustainable outcomes (Economic, process automation, safety and environmental protection).
We can track in real-time production and economic performance and automatically identify inefficiencies, enabling you with quick decision-making resulting in significant cost savings and cross organization improvements.
In Rubber Manufacturing facilities, Process cooling, Chilling and Air conditioning are the critical needs in daily production operations. Facility cooling is primarily driven by electricity, a big component of plants’ energy bills. It is possible to meet the thermal comfort demands of the plant and achieve operational and energy efficiencies that can significantly decrease ongoing operational costs.
The Industry 4.0 solution for Asset Efficiency – Chiller Digitization uses the technology to optimize volume of water and temperature setpoints while analysing the chillers, transfer pumps, cooling tower fans and cooling tower transfer pumps to maximize the Chiller Plant Efficiency.
Assets in various Industrial plants such as Roller Press, Boilers, Electrostatic precipitators, Spindles or Vibration monitoring in milling machines, heat exchangers, cooling systems are important assets/equipment that impact the overall throughput & efficiency of the Manufacturing operations.
In Rubber Industry, Compounding machines, Extrusion machines, compression moulding machines, injection moulding machines, rubber mixer, mixing mills, hydraulic press, extruder dryers and mechanical dryers, calendars, tyre curing presses, tyre moulds, tyre building machines, bias cutters are important assets/equipment that impact the overall throughput & efficiency of the manufacturing operations.
Any unscheduled breakdown in these assets impact the overall operation of the Plant, increasing maintenance costs.
The Industry 4.0 Solution, AI Powered Predictive Maintenance, Predict the remaining useful life of an Asset, provide early warning about possible failures, and forecast residual life before failure.
