For most of us, the building years of our lives were shaped by the books we read. A generation acquired its knowledge caressing through dry books with stenciled alphabets. From learning our ABCs to Shakespeare’s sonnets, Industrial Revolution ensured that its role in shaping world history through its machinery, chemicals, steam and more, is kept alive and documented via its own production of printing machines.
The Industrial Revolution paved the way for the life we know today and far surpassed the era of simplistic conveyor belts and heavy manual surveillance. Production lines employ machinery and humans alike. Industries have always stepped up with technological advancement and thereby use a plethora of devices designed and produced to meet specific tasks on factory grounds. Now is an era of warehouse robotics and sensors which not only aid in increasing manufacturing throughput but also capture different types of data, in every step of the production.
Over the years, technological advancement has mostly been through digitization, and while it gradually dropped its ones and zeros, computations became faster, devices shrunk, and we entered an era when a human trait like intelligence can also be synthesized artificially. With quintillion bytes of data generated every day, it became crucial to understand and track the data that matters, and it gradually led to the emergence of data science to look for patterns and meanings.
How can present-day industries step up with such digital advancements and thrive on it?
Say Hello to Industry 4.0
The ever-growing demand, supply-chain functioning and pressure to ensure timely deliveries keep manufacturing industries on their toes. Hence, it is essential that every process of the production cycle contributes to minimum loss, maximized production, and function like clockwork.
Most industries are already equipped with devices and sensors which, apart from functioning for which they are built also capture and send data from one unit to another. Industry 4.0 uses an existing framework of these networks of devices and sensors and gives then an AI advantage.
It uses the principles of digital automation and data exchange to make manufacturing factories function smartly. Referred now as the fourth manufacturing revolution, Industry 4.0 is the next generation of computerization which not only lets devices communicate but also provides real-time monitoring and thereby optimization.
With ProcessMiner, industries can onboard this change with ease. The SaaS-based platform picks relevant data from the start of the process to the end-quality product employs machine learning techniques to train models based on the data received and figure out the complex but relevant relationships between quality parameters. After this slow and steady phase, the customer’s dashboard is ready for easy to grasp information and charts in real-time. Moreover, the models are adaptive and evolve as per the changes done in factories. With a trained model in place, customers get recommendations based on the real-time data in their respective dashboards.
Let’s look this up in detail with an industrial case study.
Empowering Paper Industry via Real-time Predictions and Recommendations
From pulp to high-quality packaging paper, paper industries use numerous sensors across the manufacturing unit which capture real-time data every 15–30 seconds. The end goal is to ensure that paper quality, often measured in terms of their strength parameters like Mullen, STFI or Ring Crush is intact while ensuring the least usage of raw materials and generate maximum paper reels.
The platform captures relevant data from sensors during the process, and of finished quality paper of a particular grade. This process is repeated for as many grades of paper as defined by the customers and the AI model is continuously trained. Our customers define the strength parameters relevant for a particular grade of paper prior to model training and the process is then repeated for multiple grades. The model takes in data and mines for underlying complex relationships across various process data that contribute to paper quality, thereby creating a model that is not over-simplistic and hence more accurate with predictions.
All the needed data like strength parameter, paper grade, paper reel throughput is available on the customer dashboard. Over time, the model learns and defines “target ranges” for variables like Mullen/STFI/Ring Crush, raw materials weight, etc. These target ranges are the learned optimal values at which the paper production was the highest with minimum loss.
The quality of the paper reel produced is paramount in the whole process. A trained AI model in place takes real-time sensor data and makes predictions for strength and variable parameters that are bound to paper reel quality. Further, if the quality parameters deviate from their ideal values, the AI model also makes recommendations to bring them back to their desired limits.
Benefits of ProcessMiner’s Industry 4.0 Platform
- Tailor-made for your manufacturing type: Each factory is unique in its own design of production line and sensor placements. Our dashboard is designed to reflect the numbers that are relevant to the type of factory and its relevant data.
- Adaptability: Manufacturing industries undergo constant changes that can range from a change of raw materials to the degradation of machine parts. As a result, the trained models from older sensors run the risk of being irrelevant for real-time predictions and recommendations. ProcessMiner’s platform has identified this hurdle and hence designed the AI model to be self-adaptable with new sensor data. Over time, data from old sensors become obsolete and the model trains itself with new data.
- Accuracy: The model under training is fed with different kinds of data from different sensors across the process and in different types. As such, the data dimensionality is complex and hence difficult to find relationships between process parameters that matter. Our platform leaves no data unturned that can lead to the end goal — more paper, less waste. This complexity makes predictions super reliable and accurate.
- Informed decision making: ProcessMiner’s dashboard narrows down the complex and computation heavy processing of data to give relevant information related to the paper reel quality. The additional mechanism of real-time predictions and recommendations to maintain paper reel quality lets our customers make data-driven decisions.
Industries are evolving. The AI drift in digitization is here. With superior digital technological growth in place, it is a matter of time that industries would plug this growth and use it to manufacture goods more meaningfully. With access to a handy, real-time dashboard, and intelligent information, industries can thrive with reduced costs, reduced waste of raw materials, and maximized production outputs.
Originally posted on Medium.