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Manufacturing

The impact of AI on engineering manufacturing services

Unplanned downtime and subsequent disruption in manufacturing can cause significant financial loss for businesses. However, the potential of AI to reduce human errors, which currently account for 23% of manufacturing downtime, offers a promising solution. This figure is higher than any other industry, making the need for AI in manufacturing even more pressing.

Maintaining intricate supply chains, following strict delivery schedules, and meeting client commitments are non-negotiable. A survey shows that 80% of companies believe AI can reduce human errors and downtime, thereby ensuring reliable manufacturing. In fact, 30% of these companies are already reaping the benefits of AI in manufacturing. These organisations are able to achieve this with AI systems and expert consultations that facilitate CAD migration, FEA meshing, and technical publishing. Infosys BPM has developed and deployed several AI-driven solutions for the manufacturing industry, including bridging language barriers and optimising invoice processing.

This article is dedicated to exploring the benefits, case studies, and current challenges of AI in engineering manufacturing services.


Benefits of AI in engineering manufacturing services

AI in engineering manufacturing bolsters intelligent production lines by innovating, refining, and enhancing processes. This promotes better time management and reduces costs. Several other benefits include:

  • Higher accuracy and precision: AI dramatically minimises human errors and delivers a high degree of reliability in complex manufacturing processes. This helps the business adopt precise engineering tasks to provide high-quality products.With AI, the production line can create, test, and deliver design iterations faster than ever before, enhancing production efficiency and empowering businesses to be agile in formulating creative solutions.
  • Better risk mitigation and safety protocols: AI plays a crucial role in improving manufacturing safety. By predicting failures before they occur, AI increases the safety and reliability of products and processes, providing a secure environment for the workers.
  • Cost-effective manufacturing: By streamlining operations, lowering production downtime, and reducing waste, AI significantly reduces manufacturing costs. This instils confidence among businesses about the financial benefits of AI in manufacturing.
  • Supply chain optimisation: Any disruption in the supply chain can have a ripple effect on manufacturing timelines and customer commitments. AI monitors and optimises the supply chain by predicting price variations, disruptions, and changes in lead times, giving a clear visibility of resource availability and cost.
  • Sustainable manufacturing: AI creates an environment-friendly production line that reduces energy consumption and monitors the emission data. Engineers can make better design choices with a smaller carbon footprint.
  • Enhanced productivity: AI provides proactive insights and recommendations based on a vast dataset that helps the management make swift decisions. This increases productivity and reduces time-to-market.

For example, an IoT-fed AI system proactively monitors the health of machines. It alerts the maintenance teams in situations such as potential malfunction, service maintenance overdue, etc.


Use cases of AI in engineering manufacturing services

Step Up the Efficiency, Safety, and Innovation at Manufacturing Business

Step Up the Efficiency, Safety, and Innovation at Manufacturing Business

While there is a range of use cases in engineering manufacturing services, here are some of the common ones applicable across industries:


AI in CAD product design

Over 70% of manufacturing services providers are currently using Computer Aided Design (CAD) in different stages of production. Using AI, engineers can save significant time in designing a new product from scratch. They just need to upload previous designs and provide parameters for the AI model to churn the desired output.


AI in manufacturing documentation

AI allows engineers to create fast and agile documentation for frontline workers in manufacturing. Such clearly devised consolidated standard operating procedures prevent any human error or accidents.


AI in managing purchasing cycles and inventory levels

Manufacturers use AI algorithms to study historic supplier data to assess the cost and the best time to stock up on raw materials or replacement parts for machines. It can streamline warehouse operations, ensure the right inventory, and prevent from placing duplicate orders.


AI in autonomous mobile robots

Collaborative robots built using AI-enabled engineering manufacturing practices are already complementing the human workforce, reducing errors, and increasing the speed, value, and quality of products.


Current challenges to AI in engineering manufacturing services

From data security management to algorithmic biases, privacy, and ethical dilemmas, there are several challenges that a business must handle proactively while adopting AI in engineering manufacturing:

  • Data privacy and security: AI and its underlying ML model rely on large datasets (big data), which makes its security and privacy of utmost importance.
  • AI and ML integration with existing systems: Due to the complexity of AI models and the inability of legacy systems to step up, integration of the two may become a challenge.
  • Ethical considerations: These include algorithmic biases due to the data set it depends on and the virtual lack of accountability of the AI model.

Challenges may differ as per the nature of your business. The right AI implementation partner with experience in your industry can foresee the ones applicable to you and proactively provide solutions.

To tackle the unique challenges, you need a service provider with deep experience in the engineering domain, a diverse workforce, and a global footprint. Engineering process support helps businesses with:

  • Technical publishing and authoring
  • PLM process support
  • Testing factory process support
  • Specification services

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