Manufacturing companies have long used automation on the factory floor, but as demonstrated at the UiPath AI Summit 2022, they are now exploring new ways to automate processes beyond the production line. Polymer solutions manufacturer Rehau Group is a prime example. Faced with a sudden surge in sales orders, the company had to choose between hiring additional staff or automating its sales order processing. The leadership team opted for the latter, hiring a smaller group of staff to handle the immediate workload while assembling a team to automate the process.
Starting with standardized purchase orders, Rehau used UiPath Document Understanding and machine learning to extract the necessary information from emails and faxes and enter it into their ERP system. Initially focusing on select customers with consistent purchase order formats, Rehau was able to expand the scope and now automates 25% of orders for its building solutions division and 6% of orders for its furniture solutions division. To date, the company has automated the processing of 68,000 orders, saving an estimated 16 hours of manual work per day. Rehau plans to expand automation to other areas, such as shipment tracking, freight invoicing, finance, and human resources.
Global home appliance manufacturer BSH’s journey into automation began with the formation of a data science team in 2017. The team focused on creating PoC projects and promoting awareness of data science’s real-world applications before working with UiPath to create an intelligent automation group that combined RPA with AI. BSH consolidated all of its AI initiatives in 2019 under a single umbrella and now has 20 data science use cases, over 400 data scientists developing new models, and 100 automations in production. One of the use cases centers on quality management reporting, where an AI model collects relevant data from reports, and another translates the report from any of 30 languages. Other AI-driven use cases, such as internal chatbots and UiPath Document Understanding, are also in development.
Leading medical and safety technology manufacturer Drager started its RPA journey with a pilot project in 2017 and now has more than 200 automations in place. The company’s first automation use case focused on intercompany invoices, where Document Understanding and machine learning extract information from invoices and enter it into the ERP system. AI assesses the information’s validity and forwards it to an employee for review if necessary. Drager is now exploring the advantages of semantic automation.
As manufacturing companies continue to automate processes beyond the factory floor, AI and RPA will play an ever-increasing role in increasing efficiency. The potential for further automation opportunities and use cases is vast, with more and more companies adopting AI-driven strategies to meet their business needs.
