How to Optimize Factory Output Using Autonomous Machining System

(Using 21st Century Techniques to tackle a 20th Century Mindset)

A new model that is regulated with the 21st century is rapidly evolving, driven by Industry 4.0, which is a collection of various technologies. Thanks to the Industry 4.0 solution like remote monitoring, IoT is opening up new opportunities for OEM. While this digital transformation of the $10-trillion-plus global manufacturing sector will take place over a decade or more, manufacturers are going to drive bottom-line and top-line impact in the future.

The deployment that we build was the remote solution and did not need any physical presence on the factory or aftermarket sensor installations. We executed this solution, during the COVID-19 crisis; so manufacturers need not to go on factory every time. We help OEM’s to improve manufacturing efficiency by more than on an average 20% that this solution was deployed on, with only one Edge (IoT) device servicing their whole factory.

An autonomous machining system can monitor process variables and conditions across materials, machines and operators, then recognize the best corresponding optimization area. This capability to assess and monitor process variables at once enables autonomous systems to interpret plant variations that humans fight to or easily cannot estimate, or even rectify. For Instance, shifts in humidity or barometric pressure may affect site operations without human operators ever recognizing there was a change.

Autonomous machining systems can take that target-oriented performance a step further by making production goal suggestions based on current process variables.

Using IoT remote monitoring and analytics, OEMs can be easily optimized for factory output. OEMs can easily gather data from field-based equipment in real-time and predict concerns before they arise. They can then take action instantly to enhance machine performance and prevent failures. Of course, autonomous machining needs a thorough understanding of the operation of a machine, materials being machined, various types of machining processes and all of the other related systems.

The Technological Case for Autonomous Machining System

When we explore manufacturing value drivers and plot them to digital levers, we realize various opportunities for companies to generate value by increasing operational effectiveness and product innovation and unlocking new revenue sources.

Many large manufacturers are initiating to utilize data analytics to optimize factory operations, improving equipment utilization and product quality while minimizing energy utilization. Using new supply-network management tools, factory managers have a definite view of raw materials and manufactured parts flowing via a manufacturing network, which can assist them to plan factory operations and product deliveries to cut costs and enhance efficiency. Smart, connected products are sharing customer experience data to product managers to support them to predict demand and maintenance requirements and designing better products.

A major Industrial shaft manufacturing company wants to make step-change improvements in throughput. The reason behind why we consider this manufacturer to have a 21stcentury mindset is because of the benefit motive utilized to sustain their manufacturing process. Real-time performance visualization in the operator platform combined with daily quick problem solving led to a 50 % increase in production rate in one of its lines. They are able to calculate the total production, OEE, downtime and downtime reasons which will help them to improve factory efficiency and output.

By extracting data, engineers are getting new insights into the failure attributes of major equipment modes and making constant improvements in reliability. The organization expects to utilize condition monitoring and predictive maintenance, in combination with automated process controls which are made possible with IoT- enabled machine monitoring system. In a short, the owner described that it is more profitable to run his machines at twice their estimated capacity with a reduction in downtime.

Remote IoT monitoring solutions can easily be expanded to software as well as firmware. With continuous automated supervision of equipment in the field, OEMs can better recognize bugs and potential optimizations, then initiate patches or new characteristics through over-the-air updates. This practice could very well expand the lifetime of machines, improving their cost-effectiveness for OEMs and their customers.

At the end of the day, IoT enabled machine condition monitoring solution will bring several benefits.

• Larger Availability: If any critical equipment is not functioning properly then it lost overall efficiency. Predictive maintenance and quicker repairs assist to assure continuous operation.
• Increased Performance: Industrial machine monitoring systems do more than alert of failures. They also enable technicians to optimize equipment based on real-world aspects in particular use cases.
• Efficient Workforces: Customers no need to keep their own team of engineers to manage, OEMs can send maintenance technicians as per requirement instead of fixed schedules. 
• Minimized Costs: Predictive maintenance is estimated to save as much as 40% compared to a more reactive perspective. Machine monitoring system models are also more budget-friendly than large one-time purchases.
• Persistent Revenue Streams. Trends such as a machine monitoring solution will build a compact and more prolonged relationship between OEMs and their customers, protecting both from large budget variations.

As connectivity in manufacturing improves, new ways can be taken to optimize factory output. Closely placed with methodical production optimization – the lean manufacturing- data-driven optimization in manufacturing allows existing methods to be constantly implemented, analyzed and adapted. It also enables earlier blind spots in analyses to be removed and new potential for improvement to be recognized.

We are eager to lead in a new age of manufacturing, one that’s capable to use cloud technology, quickly deployable and scalable data science algorithms, remote monitoring of machines, increasing revenue and reducing costs.

The automated factory of the future is nearby, so Let’s be a key part of it !