Manufacturing is one area where automation and artificial intelligence can help reduce costs and increase output. Engage Machine Learning Development Services and your manufacturing can be revolutionized to compete with offshore manufacturers and give you a decisive edge.

Process based machine learning

In some ways machine learning is easier to incorporate into manufacturing. Unlike healthcare where there are many variables, manufacturing is relatively simpler especially if you have a process based approach specific to your segment. Machine learning development services develop ML learning programs specific to the process context and make use of data derived from the machines in use in the algorithms. This leads to higher accuracy.

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Speedy development of workable solution

Many ML developers use generic raw data to feed algorithms with the result that there are too many false positive, constant refining and adjustments. Delay is the inevitable result besides inaccuracy. Pick the right ML development services and the development gets off on the right foot.

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· Data used is data gathered from machines that will form part of the ML based automated process.

· Development takes into consideration the production floor, production methodology, stages, machines, purpose and process flow.

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· Development considers what actionable outputs are required to make ML algorithm deliver predictive capabilities.

What does this give you in manufacturing?

Predictive maintenance

Studies show that maintenance costs can be between 15 per cent and 40 percent of production cost. If you neglect timely preventive maintenance the machine fails in which case repairing costs could be 10 times the maintenance cost. Predictive maintenance saves about 12% over the cost of preventive maintenance and 40% of reactive maintenance. These numbers justify investment in machine learning development aimed at predictive maintenance. If your manufacturing unit uses very expensive imported equipment with spares that are hard to source or spares that are expensive then you could also be facing production loss if the machine breaks down. This is why predictive maintenance is gaining in popularity with its usage rising to 51%. ML powers predictive maintenance.

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The machine learning process derives data from sensors attached to the machine and PLC that control the machine. This is allied with data such as purpose of machine, variables like duty cycles and loads and other inputs to arrive at predictive capabilities to predict impending failure or identify hotspots that could be problematic. It does take time to train the ML algorithm but since it works on selected machines the work proceeds swiftly and with greater precision of outcome. Development may be based on regression or classification approach of supervised learning to map input data and output data relationship.

Where there are too many variables and production processes differ then the machine learning development services may opt for artificial neural network based unsupervised learning to deliver better predictive analysis.

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How does this benefit manufacturing?

· Once the ML based system for predictive maintenance is operational you can reduce dependence on human supervision. You save costs.

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· You avoid catastrophic failures that lead to production downtime and expensive repairs

· You can derive idea about useful remaining life of the machine.

· Malfunctions may also affect quality of product. Predictive maintenance reduces manufacturing defects.

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Machine learning development services can also help optimize product development and improve manufacturing processes.

Improving manufacturing

Manufacturing comprises an entire chain. It includes design and planning, production, supply line and marketing too. Each part of manufacturing needs data and generates data and all sections must work like a well oiled machine to deliver competitive advantage. Incorporate machine learning and you can revolutionize production. For instance, the marketing department has its finger on the pulse of the market and can know about trends that, in turn, can be taken as input to design better product or modify existing ones. Marketing can also identify trends such as increase in demand or slackening that in turn could serve as input for manufacturing and for inventory control. It is a tall order to gather data from all these sources, analyze it all and do it quickly enough to have an influence on actual production. Machine learning development services can put together a solution that will tie everything neatly and reduce dependence on human calculation and analysis which might take ages.

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Then there is the actual production process. Ideally, for example, in a CNC machine, you would expect that any component that undergoes machining would have the same precise tolerance whether it is the first off the line or the thousandth. However, in reality, the situation may be different due to various factors such as temperature variation and wear of tool tip or drive mechanisms. Use of sensors with machine learning programs would not only reduce manufacturing defects but also contribute to reduced wastage.

Manufacturing is a vast field where ML can more than prove its worth. Start by using ML development to streamline the production to market to inventory process. That in itself will bring in remarkable improvements.

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Author Bio:

Hiten Dudhatra is a Team Lead - Digital Marketing at Ecosmob Technologies Pvt. Ltd. He likes to share his opinions on IT & Telecommunication industries via guest posts. His main interest to write the content for Machine Learning Development Servcies & Artificial Intelligence. @hitendudhatra

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