Blog | Jan 17, 2022

20 Effective RPA Use Cases in Manufacturing

20 Effective RPA Use Cases in Manufacturing

How Manufacturing Companies are Succeeding with Intelligent Automation

The global manufacturing sector faces a series of significant business challenges in the years ahead. Among these are uncertainty in international supply chains, tax and transfer pricing reforms, shortages of raw materials and components, the drive for sustainability, and aging IT infrastructures.

The pandemic demonstrated the importance of agility in such difficult situations. Smart manufacturers responded by pivoting their operations to meet new market needs for products or to use different delivery channels.

As these unpredictable economic conditions continue, manufacturers must focus on maintaining market share, building agile digital supply chains, cost savings, and constructing effective partner ecosystems.

Enter Intelligent Automation (IA) and Robotic Process Automation (RPA)

To survive these challenges, manufacturers need to accelerate digital transformation with a foundation of intelligent automation. Intelligent automation enables manufacturers to standardize and simplify business processes while simultaneously freeing up their people for more strategic work.

Unlike people, digital workers don’t get bored or make human errors. They can work 24/7, 365 days a year to carry out multiple checks and follow all processes to the governed rules.

How are intelligent automation and RPA used by manufacturers?

Compared to many industry sectors, manufacturing is more prepared to use digital workers to their full potential. After all, as the early adopters of robots on the production line, manufacturers understand how automation can maximize resources and fulfill customer requirements effectively.

However, while many manufacturers have taken great strides to automate operations, challenges remain. And with issues ranging from disconnected silos to manual processes in the supply chain, there are many opportunities for automation in the industry.

In this article, we outline 20 common intelligent automation and RPA use cases in manufacturing, such as digitizing operations, creating automated supply chains, adopting the internet of things (IoT), and improving back-office systems.

Digitizing Operations

Manufacturers need to create a competitive, efficient business model where numerous people are no longer performing low-value, repetitive tasks. Intelligent automation and RPA can be used to connect systems, bringing new efficiencies to operations across a wide range of processes in manufacturing companies.

1. Production tracking

    Production tracking is a strategy used to measure, analyze and improve visibility throughout the manufacturing process. Using intelligent automation, manufacturers can develop a near real-time overview of progress on orders and the ongoing need for components or raw materials. This helps manufacturers to adopt lean manufacturing methodologies that maximize and optimize scarce resources and keep margins low.

    2. Bill of materials

      Maintaining an accurate bill of materials (BOM) is critical for manufacturers. The BOM contains the list of raw materials, sub-assemblies, intermediate assemblies, sub-components, parts, and the quantities of each component required to manufacture an end product. Using intelligent automation, manufacturers can accurately extract product data and replicate human steps required to generate an error-free BOM in a shorter timeframe.

      3. Regulation execution

        Regulatory compliance is a key process for manufacturers who face ongoing changes in everything from health and safety to cross-border trade regulations. An example of how automation can help with regulation is Belgian manufacturer Agristo, a global leader in the supply of frozen potato products. Following the UK’s departure from the EU, Agristo needed to find a way to quickly get to grips with new export regulations. Agristo deployed a Blue Prism digital workforce to handle the customs forms declaration process. Today, digital workers ensure that Agristo can properly complete customs declaration forms for 1,000 trucks every month.

        4. Auditing

          As manufacturers grow and change, existing processes, such as auditing, can become time-consuming and cumbersome. Coca-Cola’s HR group is running HR audits in SAP, enabled by Blue Prism’s intelligent digital workforce. The beverage giant has automated more than 50 processes across multiple SAP systems and delivers services 24 hours a day with no additional staff required.

          5. Customer service & support

            Customer experience can be improved through efficient purchase order processing, responsive customer service and enhanced quality assurance. An example of how intelligent automation can help with customer service is Sysco, the largest distributor of food and food-related products in the world. They embedded intelligent automation into their distribution network to help better serve their 600,000 clients. This network was placed under huge strain when the pandemic disrupted the world’s economy, so Sysco responded by expanding its automation efforts to more than 60 digital workers. This resulted in 6.2 million transactions being processed and returning more than 250,000 work hours to the business.

            Transforming ERP/SAP

            Enterprise resource planning (ERP) platforms such as SAP have traditionally been adopted by large manufacturers to support business operations. However, ERP systems can be difficult and expensive to adapt to changing requirements. When replacement of platforms is not a viable option, manufacturers can use intelligent automation and RPA to transform their ERP. Using bots, processes can be automated and system functionality improved by gathering the data they need from core systems without disturbing legacy IT resources. 

            6. SAP/ERP operations

              Modern manufacturers use ERPs to support planning and managing of operations within their business. But, due to the myriad of areas ERPs manage, they are often complex and costly to manage manually. To simplify management and increase efficiency, organizations are turning to automation as a solution. An example of this is AGCO, a leading global manufacturer of farm equipment, including brands such as Massey Ferguson. As with many users of large ERP systems, AGCO found that journaling was tying up a significant amount of its human workers’ time. It needed a smarter way to complete its journaling, reducing its overtime costs, but without jeopardizing the accuracy of its systems. Today, journaling is facilitated by multiple Blue Prism digital workers, who are “managed” by another digital worker that schedules and oversees the rest of the digital team.

              7. Migration from legacy ERP

                The fact that support for SAP ERP Central Component (SAP ECC) ends in 2027 means many manufacturers are moving to SAP S/4 HANA. This is proving difficult, with multiple options that invariably take years for many organizations to complete. However, the migration process provides an opportunity for organizations to take a critical look at current ERP strategies and how automation can help move them forward on the path to digital transformation.

                8. Data migration and management

                  Intelligent automation makes ERP migrations easier by orchestrating and validating data migration across databases. British baking and flour milling business, Hovis, was laboring under the complexity of many disparate systems and processes. Wholesale system changes would take too long and were costly to implement. Their workaround was to manually enter data to bridge the gaps, which relied on humans bridging siloed systems. By employing intelligent automation, Hovis has all but eliminated errors in master data and scheduling updates.

                  Creating Digital Supply Chains

                  Today’s manufacturing landscape is made up of independent silos. Getting key data from all these silos — as well as older, disparate systems — can be a challenge. Additionally, it can require a lot of time-consuming manual processing and additional personnel to gather this data. With a digital supply chain, manufacturers can de-silo processes and create a data lake/process mining area where key insights can be gained.

                  9. Supply chain demand planning

                    Predicting demand of goods and materials across multiple geographies in the supply chain requires effective digital integration and connections. Automation breaks down supply chain silos and provides insight, so goods and materials are ready where they’re required. A leading supplier of steel and metals, Norsk Stål, showed what can be achieved with RPA and intelligent automation in supply chain demand planning. Across their plants, a team optimizes how to effectively manufacture steel products to meet customer deadlines — and to minimize waste. Each day, production planners provide a digital worker with an estimate of the maximum workload for the plants. The digital worker then gets the approved orders for steel products in their ERP, calculates the optimal production, and sets up a manufacturing plan for the plant before the morning shift starts.

                    10. Freight management

                      Machines capture essential data on the factory floor, but it’s often trapped within systems that aren’t always easy to access. Intelligent automation provides a fast, agile way to access data and integrate it with other systems — saving time and money. Manufacturing organizations can expect to achieve enhanced freight management processes, such as route optimization, freight accounting, and freight claim management.

                      11. Inventory management

                        Each morning before the workday begins, digital workers at chocolate manufacturer, Hershey, run a process that captures every mislabeled product and informs the distribution center and supply planning personnel who can quickly and accurately correct inventories. Digital workers perform the more repetitive checks between different applications, providing a much more accurate and consistent service than when humans managed the process.

                        Adopting IoT

                        12. IOT & Predictive maintenance

                          Predictive maintenance solutions are often delivered by rules-based systems which result in frequent false positives; they’re less effective and less efficient. Using advanced machine learning with RPA enables faults to be predicted in advance with much higher accuracy, resulting in higher equipment uptime at a lower operational cost.

                          Improving back-office processes

                          While manufacturers are adept at building robotics into shop floor processes, too often, the back office continues to rely on people to carry out repetitive tasks, such as credit and collections management. Yet, with estimates showing that as much as 70% to 80% of such tasks can be safely automated, there are plenty of opportunities to deliver performance improvements without investing in additional resources.

                          13. Contract management

                            RPA bots can create, update and alert manufacturers on supplier contracts. This empowers employees to proactively renew contract agreements with suppliers and ensures enough time is available for renegotiation.

                            14. Automate Invoice processing

                              By automating processes such as invoice creation, checking and processing using intelligent automation, manufacturers can reduce errors, improve productivity and improve customer experiences.

                              15. Order management

                                Simplifying and automating order management enables manufacturers to streamline internal processes. This ensures the right data feeds into operational systems, such as digital supply chains and demand forecasting.

                                16. Credit & collections management

                                  Streamlining collections processes is essential in reducing bad debt, cutting associated costs and improving the end-user customer experience. Manufacturers can use intelligent automation to pull together customer information, such as credit records, prior to collection action proceeding.

                                  17. Account changes

                                    Manufacturers can facilitate self-service or streamline customer service data input across systems with intelligent automation. This ensures they always have correct data in place for customers and that it flows through every process involving those customers, avoiding costly mistakes and workarounds.

                                    18. Supplier onboarding

                                      Carrying out compliance checks and gathering information to onboard suppliers are time-consuming and resource-hungry processes. And tasks are often completed in serial by different teams, so the resources needed to ready a new supplier for business can have an extended timeframe. Instead, manufacturers can train digital workers to seek out relevant data as part of a parallel process that is both speedy and accurate.

                                      19. Performance reporting

                                        Digital workers can build reports to demonstrate regulatory performance and adherence to SLAs. Swiss industrial manufacturing giant, ABB, used intelligent automation to gather and create over 200 reports each morning. This provided staff in over 25 countries with the insight they needed to improve their performance.

                                        20. Quote management

                                          Intelligent automation enables manufacturers to provide on-demand quotes automatically, minimizing delays and improving customer experience. AGCO used intelligent automation to handle its critical quotation process for revenue generation. It was previously taking up a huge amount of time of staff to complete each quote. AGCO wanted to optimize the process, giving its staff more time to focus on negotiating better contracts. Now, when a request for a quotation is received, a digital worker reads the email, retrieves data, updates systems, and sends the quote. This saved thousands of hours, giving time back to staff to focus on more valuable tasks.

                                          Conclusion

                                          As the 20 use cases for intelligent automation and RPA outlined above illustrate, the application of these technologies can deliver benefits across nearly every aspect of manufacturing.

                                          The most effective results we’ve seen in the sector have some common themes, including the adoption of a center of excellence (COE) responsible for governance, security and sharing best practices across the organization.

                                          According to Deloitte, in its 2022 Manufacturing Industry Outlook, “Manufacturers looking to capture growth and protect long-term profitability should embrace digital capabilities from corporate functions to the factory floor.”

                                          In the challenging and uncertain market in which manufacturers currently operate, an integrated, centralized approach to intelligent automation will deliver the biggest dividends.

                                          To find out more about intelligent automation and RPA in manufacturing, download our whitepaper here or contact one of our experts below

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