The advent of Industry 4.0 brings with it the extensive use of smart digital technologies, like the Internet of things, cloud computing, robotics, software, automation, and cognitive technologies such as AI & machine learning, in manufacturing. Enterprises are becoming more open and aggressive in using these technologies to improve operational efficiency, reduce the mudai involved, and go lean to maintain their competitive edge. Manufacturers realize that digital technologies are essential for them to reduce costs, improve the bottom line, and also add to their topline growth. Resultant smart factories, better insights into processes, and optimized supply chains make manufacturing more efficient and poised to deliver better outcomes for industry players and customers alike.ii
In this article, we look at some use cases of manufacturers using the power of Automation, AI, and Applications of AI to become more efficient and customer-focused.
A leading aircraft manufacturing and parts distribution company in the US, dealing with hundreds of suppliers and customers, struggled with its Purchase order (PO), Sales Orders (SO) processing. The existing process, handled by a large operations team and sales representatives, was predominantly manual and error-prone. Adding to the challenge was the complexity of the PO itself. A single aircraft contains lakhs of partsiii , and it’s normal for a single PO in the aviation parts business to have hundreds of line items to place an order for thousands of parts.
The process could be made more efficient with Intelligent Document Processing and Robotic Process Automation (RPA). EdgeVerve used Nia DocAI combined with AssistEdge RPA and automated the entire process.
As a result, the customer could eliminate the as-is 2-step process of data entry and validation, extract data with 80-90% accuracy, reduce AHT by 50%, and automate over 16,000 transactions per month. This saved over 43,000 hours of manual effort and subsequent costs.
Similarly, one of the world’s largest electronics companies and a leader in healthcare technology was looking to harness the power of digital transformation to accelerate its next phase of growth. They were looking at RPA to automate their Finance Planning & Accounting (FP&A) operations in the Record to Report (R2R), Order to Cash (O2C), and Procure to Pay (P2P) processes as well as Reporting and Consolidation activities. AssistEdge RPA automated 35 complex use cases saving 32,000 person-hours.
This implementation is one of the most complex, large-scale, and successful RPA implementations across the industry, with 400+ bots running in a High Availability setup 24X7 and more than 90% accuracy.
When applied to client prospecting and building sales intelligence, the use of intelligent technologies could act as a new growth engine for the customer. A leading Aerospace Parts Manufacturing company relied on manual analysis of past trends to identify cross-sell opportunities. Their existing process had limited intelligence and relied only on internal data sources for building intelligence. This led to inaccurate opportunity identification.
The EdgeVerve team helped improve the process and make it more accurate. Using the NIA platform, we blended information from key internal and external sources, especially on projected customer fleet and its characteristics. It contextualized the ML-based recommendation system built by correlating the purchases from customers with similar fleet profile AND products strongly associated and are most likely purchased together. Products-to-aircraft associations were generated as additional intel for the sales team.
As a result, the customer could tap whitespace opportunities for 46 priority customers in the EMEA region. New verified opportunities worth USD 8 million were created annually for the EMEA region, and recommendations achieved an average hit rate of 70%.
A leading Forklift Manufacturer in the US struggled with inefficient, manual processes. Precious SME and associate time, which could have been deployed towards business growth, was spent on doing mundane and repetitive tasks, leading to a lot of muda. The client deployed intelligent automation to optimize processes for its Fleet, Service Parts, and Dealer Development departments.
The Fleet department’s invoice coding process was one of the automation candidates. The process involved a rule-based validating and coding of invoices received from dealers. The process calculated labor hours and then either approved the invoice or sent it for manual review. This entire process, which involved reading from the repair description, was automated using AI technologies like NLP and text analytics. Machine learning algorithms were used to predict the labor hours for the repair. The process is now touchless and auto-approves invoices. Exceptions that require manual review also have a note to the reviewer that notifies them of the issue. This saves time and also has a saving potential of USD 155,000 per annum.
Technologies like AI and automation have the potential to transform your enterprise operations and manufacturing supply chain processes. The need is to follow a structured approach to identify these opportunities, prioritize the ones with higher ROI, and over time make your organization processes Agile and lean – in turn improving the customer experience and realizing the true potential of Industry 4.0.