RPA in manufacturing: use cases, benefits & challenges

Even with comprehensive warehouse management systems in place, managing inventory can be a time-consuming and error-prone task. Inventory managers and warehouse staff still have to manually enter information from delivery notes into inventory management systems, which significantly slows down business processes.

To free up employees from manual data entry, companies can use RPA bots to automatically update stock levels in the inventory management system. An RPA bot processes the scans of delivery notes using optical character recognition (OCR) technology and promptly updates information about raw materials inventory levels.

For accounting departments, the bar is often set extra high: employees need to process voluminous financial data, validate its accuracy, and rule out any mistakes that can bring losses to the enterprise.

Therefore, manufacturers can implement RPA software to automate most of these mundane activities. For example, bots can simplify invoice processing by extracting financial data from digital documents as well as from the scans of physical invoices. By minimizing time-consuming manual data entry, RPA software helps manufacturers increase financial data accuracy. Also, RPA streamlines accounts payable and accounts receivable management by automatically retrieving vendor data, initiating the payment, generating customer bills, and sending payment reminders to the clients according to the corporate credit and collection policy.

Whether the manufacturer launches a new product or reformulates the products in the current portfolio, the accurate list of components or ingredients should be reflected in bills of materials (BOMs). However, creating new BOMs or constantly keeping existing BOMs up-to-date can be a time-consuming task. 

An RPA bot can automatically extract relevant data, like ingredient names, part numbers, costs, and quantity, from various sources, including technical designs, product specifications, and inventory records, and start the BOM creation/update processes in seconds.

By implementing RPA to handle time-consuming customer relationship management tasks, manufacturing companies leave more time for their sales representatives and support agents to build trust with clients. For example, sales departments can use RPA bots to enhance the onboarding journey for new customers. An RPA bot can monitor order requests in real time, and if there is an order from a new customer, the bot can initiate contract creation. It scans the incoming order to detect the information required to create a new contract, such as billing address or payment method information. Then, the bot enters it into a respective contract template and sets up a new customer account.

Order management is a tedious process, which comprises many rule-based tasks, which can be streamlined with RPA.

Manufacturing companies can use RPA to process quote requests and purchase orders with NLP (for textual information) and OCR (for document scans) capabilities and extract order information. Then, sales teams can use the extracted information to prepare quotes or place new orders. After that, RPA bots populate invoice templates with information from the incoming purchase orders and generate shipping invoices.

For a manufacturing enterprise, timely order delivery contributes to a stable cash flow and increased customer satisfaction. RPA bots can handle various freight management tasks, including creating template-based contracts for logistics companies and scheduling deliveries.

To keep customers updated on order statuses, companies can use RPA bots that automatically retrieve delivery time estimates from the logistics management software and send respective customer notifications using ready-made templates.

Manufacturing enterprises must regularly report on their financial, sustainability, and production metrics, including assembly lines efficiency, equipment and physical robots downtime, and detected quality control issues. Robotic process automation can handle it with ease, generating detailed reports for future audits. 

RPA bots enhanced with natural language processing can extract relevant details for the reports, including from unstructured data (e.g., emails, notes), which significantly speeds up data preparation and decreases report creation time. 

As a manufacturing business grows, the amount of data that needs processing increases. Instead of hiring new employees, enterprises can entrust laborious data management activities to RPA bots. 

RPA bots can be configured to remove duplicates, cleanse and reformat corporate data as well as structure and prepare it for data analytics or migration. RPA bots enhanced with AI capabilities can process unstructured data as well, including invoice scans, emails, and audio and video content, reducing the likelihood of human errors and contributing to consistent data processing. According to Strategic Market Research, 85% of companies experience a boost in data accuracy after RPA implementation.