Driving Digital Transformation in the Manufacturing Sector with AI and ML

Cutting-edge, disruptive technologies like Artificial Intelligence (AI) and Machine Learning (ML) are driving process automation changes that provide corporates with unparalleled abilities to make faster decisions, and drive timely outcomes and deliveries. Manufacturing is a segment that has been slow to change because of its long association with legacy systems and complex processes.

What the industry did not expect is that disruptive changes are transforming all layers of the industry. Manufacturers are facing challenges to improve product quality, minimize downtime, meet highly variable demand, and cater to personalized products that require high automation efficiency. AI and ML are playing a big role in helping manufacturers transform to achieve these goals.

From supply chain management to predictive maintenance, manufacturers need technology-driven innovations that can integrate processes and drive seamless operations. Coupled with the need to improve employee efficiency and drive R&D efficiency, the manufacturing industry faces multiple challenges to meet the growing demands of its customers.

Building Business Value with AI and ML

Bringing AI and ML technologies into the manufacturing sector can be a dream situation, given that the benefits range widely from improving operational efficiency to driving bottom-line growth. Let’s take a look at how each of the below parameters are influenced by AI and ML technologies.

1. Sensitizing Predictive Maintenance

According to a PwC report, ML analytics can improve predictive maintenance processes by 38% in the next five years. Through improved process visualization and automation, the algorithms can help manufacturers expect a steep rise in their growth rate. By reducing supply chain forecasting errors, companies can achieve better product availability, and more efficient transport and warehousing administration. 

2. Raising the Cost-Benefit Value

Integrating AI and ML algorithms into procurement data can aid in strategic sourcing and cost management. Machine Learning-based root-cause analysis can bring down annual predictive maintenance costs, while AI-powered predictive maintenance ensures seamless operations and high yields. AI-based optimization can reduce machine downtime and inspection costs. This improved accuracy causes a ripple effect, sometimes contributing up to 50% reduction in the manufacturing costs. 

3. Asset management and Inventory Optimization

Adopting AI and ML can drastically increase your asset tracking accuracy and inventory monitoring, across global locations, thus enabling shop floor teams to gain increased visibility into their supply chain movement.

Inventory optimization through ML algorithms can enable marketers to manage their demand supply, taking into account time-to-market variables. Real-time monitoring of shop floor operations offers the necessary insights to achieve optimal production schedule performance and higher visible control on maintenance activities.

4. Leveraging Real-time Testing Intelligence

One of the major roadblocks in manufacturing is the testing stage. Achieving accurate prediction of calibration and test results using machine learning algorithms enables easy isolation of bottlenecks, and streamlining of the end-to-end test processes. AI and ML can certainly enable manufacturing companies to go past the boundaries of traditional tools and processes, to procure real-time intelligence that can drive real-time accelerated growth.

5. Raising the Operational Efficiency Bar

Embracing AI and ML leads to reduction in downtime due to human errors and ensures streamlining and linking of all in-house and subcontract processes. This results in the company gaining more time for innovation and R&D to cater to new market segments. A powerful operational advantage is that AI and ML-based predictive maintenance brings factory downtime to almost zero for greater efficiency. 

Embracing AI and ML

Disruptive technologies such as AI and MI have a positive impact on manufacturing processes, delivering multiple benefits to drive business growth. InApp provides smart digitalization strategies setting the stage for long-term growth and market leadership. InApp solutions offer automation benefits, NLP capabilities, object recognition features, and real-time predictive insights. We help you choose the right AI solution that can drive digital transformation at a fast pace, and one that suits your current business needs.

Interested in exploring a transformative digital solution with us? With over 15 years of experience in the manufacturing sector, we would be happy to help. Click here to get in touch with us.



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