RPA in Manufacturing: Game-changing Benefits and Use Cases With the Fastest ROI

Industrial owners are losing a fortune and seeing their productivity plummet due to mundane repetitive manual tasks, inevitable human errors, and employees drowning in spreadsheets. RPA in the manufacturing industry helps to root these issues out.

With ever-present budgetary constraints and tight deadlines, RPA stands out as a relatively cost-effective, fast, and low-risk way to strengthen operations. It’s less complex than other enterprise automation technologies, like smart physical robots within production sites or digital twins that mimic factory floors. 

Organizations report a typical payback of 250% within two or three quarters after RPA adoption. Pretty impressive, isn’t it? Some high-performers have even achieved a 380% return on automation investments.

This is just a small part of why spending on robotic process automation software is forecast to grow at a CAGR of 36.6% from 2022 to 2032. 

Having mastered RPA inside and out, our experts are eager to share hard-won insights distilled from over 20 years on the front lines. Let’s delve into the mechanics of RPA, its transformative benefits, and real-world applications, illustrating how this technology is propelling the industry toward excellence.

What is Robotic Process Automation in manufacturing, and how does it work?

Robotic process automation (RPA) is a technology manufacturing businesses use to automate high-volume, repeatable tasks.

Using scripts that emulate human actions, software robots are there for you to perform repetitive tasks. They log into enterprise applications, move files, open and send emails, fill in forms, and tackle all that white-collar worker’s daily routine.

The sweet spot for RPA lies in automating rule-based, straightforward, and mostly high-volume tasks. Completing them manually is time-consuming, error-prone, and far from creative yet vital to keeping the factory running. Meanwhile, bots do them all way faster and without lapses.

See it in action:

• Before automation: a manufacturing company receives hundreds of invoices from various suppliers each month. Employees manually input invoice data into the ERP system, verify details, and process payments. The process itself is a bottleneck, often leading to delays and inaccuracies.

• After automation: an RPA bot handles the end-to-end process in seconds, signaling only in case of exceptions where manual validation is required.

There is also a more advanced form of RPA called cognitive automation. It aims to overcome the limitations of traditional RPA by applying more intelligence to tasks, hence adding some recognition and analysis capabilities.

Four benefits of RPA in manufacturing you can’t ignore

RPA turns out to be a game-changer for the manufacturing industry in many ways. By streamlining complex operations, enhancing precision, and slashing costs, it empowers manufacturers to pivot from routine tasks to strategic innovation.

Lower operational costs

Wiping out costly errors and freeing up staff from mundane duties makes RPA an instrumental add-on to your cost-reduction strategy. 

Typical savings on current operational costs range from 25% to 80%, which can translate into tens of millions of dollars annually for some organizations.

Moreover, the speed and accuracy of automation help reduce administrative, prevention, appraisal, and internal/external failure costs — the list can go on and on. 

Enhanced regulatory compliance

Apart from RPA-driven cost reduction, organizations also reap benefits like improved compliance, recognizing the impact of the technology on enhancing efficiency. 

With RPA’s capability to cross-reference raw materials and testing results against regulatory requirements, update compliance documents in real time, and, overall, facilitate adherence to regulations, meeting even stringent standards, such as FDA’s Current Good Manufacturing Practice (CGMP) or equivalent EU legal guidelines, becomes a breeze.

Our client, a leading manufacturer with production plants across the APAC region, stated: “Taking care of compliance and internal checks from the outset of our RPA journey was a brilliant move. Deploying multiple bots has boosted overall process quality and ensured reliable execution.”

All aspects of the manufacturing process can be automatically tracked for compliance with established standards, safety guidelines, legal requirements, and environmental regulations.

Increased productivity

RPA transforms how dozens of routine but critical tasks are handled. The tireless digital workforce completes these tasks in seconds with near-zero error rates. 

Automation can be especially helpful when organizations experience a labor shortage. With RPA in place, all operations run efficiently even during high-volume activity and peak workloads. 

Up to an 85% improvement in time efficiency and saving over 1000 hours or 199+ FTE days can be achieved simply by replacing humans in data entry tasks. Imagine the productivity gains after automating other tiresome back-office routines.

Any way you slice it, the outcome is freeing up thousands of labor hours yearly and increased productivity as workers focus on higher-value, meaningful work.

Improved quality and accuracy

High quality is always a matter of a strong reputation and profitability. Cost of poor quality (COPQ) can amount to 15-20% of sales revenue, with some reaching up to 40% of total operations.

Let’s recall traditional Bill of Material (BOM) management, which often suffers from manual errors. Incorrect quantities or assembly instructions, inconsistent updates, and difficulty tracking changes lead to defective products, wasted resources, and costly rework. Automation software accurately updates BOM data and transfers it into ERP systems, making sure nothing is overlooked, even when changes occur. Zero — that is the number of errors in BOM management you can expect after adopting RPA.

In production lines, RPA maintains stringent quality specifications, reducing defects in final products. Bots consistently perform quality inspections, minimizing the risk of human oversight. After implementing RPA in their quality assurance processes, most of our clients reported up to a 60% reduction in product defects.

Use cases where RPA in manufacturing pays off

Manufacturers turn to RPA for value-creation opportunities in time-consuming and repetitive processes such as procurement, inventory management, and payment processing. Below, we list examples of RPA manufacturing use cases with the top tasks primed for automation.

Back-office tasks

Purchase orders (PO), status reports, avoiding duplicates, updating invoice records… The manufacturing back office thrives on documentation. Thanks to RPA, a range of operational activities can be completed fast and flawlessly.

Invoice processing

Instead of manually sifting through files and matching numbers, employees can focus on more strategically significant tasks, leaving the meticulous checks to robots.

RPA bots can automate invoice processing by extracting data, validating information, and routing invoices for approval. Here’s a breakdown of what exactly they are capable of:

• Downloading and extracting data from supplier invoices using Optical Character Recognition (OCR) technology
• Verifying data accuracy by comparing it with purchase orders and product catalogsRouting invoices for approval based on predefined rules (for example, amount thresholds)
• Generating automated payment schedules and sending them to the accounts payable department

Leading manufacturing companies using RPA-enabled invoice processing report that over 80-90% of all invoices are handled without requiring manual inspection. 

An invoice automation project, delivered by the *instinctools team for a multinational manufacturer resulted in $0.9 million in annual cost savings.

Order fulfillment

An automated process of order fulfillment is more accurate, as it fends off errors from the outset. What are the common order-related tasks manufacturing companies can automate?

• Data entry of customer orders received through various channels (email, website, etc.)
• Order verification and stock level checks
• Automatic generation of picking lists and documents from shipping processes
• Sending order status updates to customers

Data entry

Repetitive data entry tasks across existing systems are the most obvious target for automation. Such RPA examples include:

• Updating inventory databases with new stock entries (e.g., raw materials)
• Entering production data from machine logs into relevant software
• Transferring customer information from web forms to CRM systems

When a fast-growing beverage distributor faced challenges in managing data flows within their newly implemented enterprise application, they turned to us for a solution. To address the client’s data entry and management hurdles, we deployed RPA software, streamlining data quality checks and automating the input of new product versions into their new ERP system. This strategic move replaced a labor-intensive process with a single, highly efficient bot, amping up operational efficiency and setting the stage for scalable growth without increasing the headcount.

Production line support

RPA solutions enhance productivity along production lines, helping to accelerate operational tasks and phase out manual process flaws.

Quality control checks

Automation tools are used widely in manufacturing tasks aiming to ensure the highest quality possible:

• Collecting data from automated inspection systems, such as vision cameras
• Identifying potential defects in the extracted data based on predefined parameters
• Flagging faulty products and generating reports for further investigation

Generating reports

Automation in the manufacturing sector has long outperformed manual processes in gathering relevant data, visualizing all critical production KPIs, and then delivering final reports to the right stakeholders. RPA speeds up the production planning and reporting by:

• Collecting data from different independent systems on the assembly line, including metrics like machine performance or production output
• Formatting the data into reports with charts and graphs
• Sending reports automatically to relevant personnel, such as production managers, quality control teams, and others

Managing inventory levels

Poor inventory turnover rates, overstocking, and stockouts are nightmares for manufacturing operations managers. RPA bots put them back in control by:

• Monitoring stock levels in real-time based on production data and sales information
• Automatically generating purchase orders for low-stock items
• Tracking incoming and outgoing inventory shipments
• Forecasting & estimating inventory levels

Supply chain management

Due to global geopolitical tensions, a supply chain may become a roller coaster for manufacturers. Automation technologies, including RPA, help companies gain as much control as possible over globally scattered supply chains.

Supplier communication

RPA solutions can streamline repetitive tasks related to supplier communication, including:

• Sending automated purchase orders to vendors
• Monitoring supplier performance based on delivery schedules and quality metrics
• Triggering automated email reminders for overdue deliveries

Order tracking

Automating repetitive tasks in order tracking facilitates transparency in managing the flow of goods from the production line to the warehouse. RPA bots can do the following tasks:

• Tracking the status of shipments from suppliers in real time using tracking numbers
• Generating automated alerts for any delays or deviations from expected delivery times
• Updating internal inventory systems upon receipt of goods

Once again, manufacturing process automation covers various tasks within inventory management, keeping up with regulations, processing documents, streamlining the supply chain, and supporting production needs. The automation potential of these areas delivers the highest business value.

Empowering intelligent automation amidst the industry 4.0

Combined with AI sub-disciplines like machine learning, computer vision, optical character recognition (OCR), and natural language processing (NLP), AI-backed RPA solutions bring more value to the manufacturers’ table. Artificial intelligence helps tackle many complex tasks that RPA alone would struggle to complete.

While RPA can be considered the “doer” of tasks, AI is more about the “thinking” and “learning” sides of things. 

AI-enabled agents provide a more advanced level of industrial automation and helps scale your enterprise intelligence. Once you add automation components to certain routines, you can start identifying more complex tasks that require decision-making, pattern recognition, and adaptation to new scenarios. For instance:

• Procurement: predicting pricing trends, analyzing supplier performance, etc.
• Quality control: processing inspection data, identifying defect patterns, predicting equipment failure, etc.
• Production support: optimizing production schedules & inventory management, forecasting demand fluctuations, etc.
• Supply chain management: recommending alternative suppliers, predicting potential disruptions based on historical data, etc. 

RPA journey made easy with these 4 steps to start with

Your RPA implementation should not necessarily start with enterprise-wide automation. Many of our manufacturing clients began with targeted transformations in specific functional areas. Pilot success often fuels wider adoption with far-reaching goals.

Each company moves at its own pace, in its own way. However, there is a set of common steps to ensure all-encompassing RPA implementation regardless of the organization’s maturity level or scalability plans. 

1. Identify and document recurring tasks and procedures that can be automated

Examine your processes and gather feedback from employees across different departments to comprehensively understand their pain points. 

Look closely at your current workflows and identify time-consuming tasks ripe for automation. Pay special attention to repetitive, rule-based administrative tasks with clear steps and straightforward goals. 

You can explore the above-mentioned robotic process automation examples as a starting point or seek professional guidance to identify additional opportunities for your future automated manufacturing.

2. Determine if cognitive automation is necessary

Are RPA bots enough to cover tasks you’ve defined for automation? Or maybe realizing more advanced capabilities, say, human speech recognition, image detection, unstructured data analysis, or AI chatbot integration is needed? 

If yes, then you have to look for additional AI/ML expertise.

3. Search for a suitable RPA solution

Explore relevant manufacturing automation case studies and examine how your peers approach automation. 

While your specific scenario might require fully custom software or customization of ready-made  RPA products, don’t be discouraged by the lack of internal competencies. 

Consider working with technical partners to bridge any expertise gaps. There is often added value in the form of ongoing maintenance and scaling your solution into a corporate-wide initiative as your needs evolve.

4. Assess the costs of integrating the solution

Once the project scope is defined and the team is assembled, it’s time to estimate the expected timeframe and costs. Then, calculate ROI to determine whether the project aligns with your goals and stays on course with profit projections.

A pure cost reduction exercise or an opportunity to invest in enterprise-wide digital transformation? RPA can do both for your manufacturing business

Implementing RPA requires investment and C-level buy-in, but the payoff can be swift and sweet, assuming you have clear goals and engage the right people in the change process. 

The benefits of manufacturing automation go far beyond merely having a cheap and reliable digital workforce for rule-based tasks. Robotic process automation in the manufacturing industry can become a crucial building block of your company’s digital transformation, paving the way for sustainable growth and long-term success. 

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