Why manufacturing automation alone falls short of digital transformation

April 25, 2022 | 6 minute read
Joel De Guzman
Senior Product Marketing Manager, Oracle
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We often hear that factory automation results in agility, resiliency, and business success—but is it true?

If profitability and customer satisfaction are key measures of business success, automating production may not be enough.

What else do you need?

Industry 4.0 is a key objective for many manufacturers. Robots and automated material handling systems are common in many factories. Manufacturing execution systems (MES) and other operational technology (OT) software that support Industry 4.0 initiatives allow manufacturing managers more control and consistency over the products they make.

Yet the value of these technologies alone can fall short of expectations. Executives are looking to what many call smart manufacturing to do more than just automate manual processes, improve quality, and increase production throughput. In fact, the Smart Manufacturing Strategy and Implementation Trends Survey from Gartner shows “support supply chain agility” and “improved flexibility” among the top expected benefits of smart manufacturing. These outrank the more traditional benefits like “improved capacity utilization” and “labor productivity.”

However, these benefits can only be achieved by integrating manufacturing applications with enterprise applications. The picture gets better if they all are part of an integrated suite like Oracle Cloud Applications.  Running these systems on a common data model and unified enterprise data architecture allows the applications to share, consume, and contextualize both operational technology (OT) and IT data for accurate production planning and efficient execution. The added value is that advanced technologies such as the Internet of Things (IoT), data analytics, and artificial intelligence/machine learning (AI/ML) can be embedded in this framework using standard communication protocols and computational efficiencies to improve the quality of decision-making.

In the demo, Excel with Digitally Connected Manufacturing, Surya Kommareddy and I showed a fully automated manufacturing demo using robotics, IoT, data analytics, and AI/ML quality inspection. The demo runs for only 20 minutes, so I encourage watching it to see how shop floor operations can be integrated with Oracle applications. You’ll also see how Oracle helps reduce data latency with the use of regular internet connections and our cloud architecture.

Creating the digital thread

The shortage of skilled manufacturing workers has led companies to accelerate the automation of many manual operations. But unless these operations are the limiting constraints in a production line, the overall factory output often does not increase, nor has the factory been made more resilient to any out-of-cycle changes in demand or raw material availability.

In our demo, we show that full automation without manual intervention can be achieved in a production line equipped with sensors connected to Oracle Cloud Applications through standard software interfaces. eCommerce and order management applications are integrated, so the digital thread spans different business functions—such as sales, supply chain, and finance—to enable full, lights-out manufacturing. This data-driven architecture links information together and provides a single source of truth for a company’s products—at any instance of time.

Why is this important?

This digital thread lets different teams share data about sales orders, inventory, machines, and human resources in real-time. Minimal data latency between process steps, automated detection of quality issues, and anticipation of equipment failures (predictive maintenance) are made possible. This helps your business meet customer expectations, become more resilient to customer demand or supply changes, and frees up more time for things that help the bottom line, like innovation. Even better, innovation is not just limited to one department but can be done across any line of business.

Can this scale to a full production line?

A manufacturer would need more reliable industrial-grade equipment, material handling systems, and commercial-quality sensors for full production—but from a software perspective, the demo already uses the same Oracle Cloud eCommerce, Order Management, Manufacturing, and Analytics that are available with commercial licenses. We use standard software interfaces like the OPC Unified Architecture (OPC UA), an open-source standard for data exchange from sensors to cloud applications. Message Queueing Telemetry Transport (MQTT), a lightweight messaging protocol that connects devices on the Internet of Things, is also used to ensure interoperability with enterprise applications.

A single source of truth

It’s important to have one source of truth across all applications so that you can make quick decisions without needing to manually reconcile your data. This agility supports supply chain resiliency and contributes to sustainability goals. Overproduction due to canceled orders is minimized and material waste due to quality defects are reduced. 

Throughout the entire business process in our demo—from customer order generation up to finished goods production—the Oracle suite of applications all leverage a unified data model to ensure there is a consistent single source of truth across the digital thread. The sales order and corresponding work order created from the eCommerce storefront transactions are linked, and updated in real-time with the latest status throughout the various Oracle applications such as Order Management, Manufacturing, and Quality Management.

In another example, equipment assets connected to the Oracle Cloud Maintenance application with Oracle Asset Monitoring Cloud are visible and consumable by other Oracle Supply Chain Management and Financials. The availability of equipment resources can be taken into account in production scheduling runs, resulting in a more accurate schedule. Spare parts can be ordered easily through integrated supplier e-commerce “punch-out” catalogs, without having to generate separate purchase requisitions.

Industry 4.0 technologies in action

Finally, let’s not discount the role of advanced technologies such as cloud computing, IoT, data analytics, and AI/ML. Cloud computing, together with the unified data model, ensures minimal data latency between OT and IT applications, especially if they are built from the ground up as integrated suites.

IoT allows for the constant connectivity of equipment and material. A digital twin representation of the production line, and even a network of factories, can be built for complete visibility into production status. Even labor resources can take advantage of IoT connectivity with mobile devices and wearables. Line stoppages are immediately detected, raw material waste reduced, or worker accidents prevented. IoT also results in large amounts of operational data. Without analytics, only the tip of the iceberg is visible and actionable. Data analytics—if properly done with data warehouses and intuitive dashboards—help users visualize and contextualize their operational data to make better enterprise-wide decisions.         

In our demo, we also show how AI/ML is used to inspect the quality of a laser engraving. The engraving is “inspected” with a machine learning model in the Oracle Machine Learning and AI Service. In this case, quality data is then stored and tracked in Oracle Cloud Quality Management. As the machine learning capability quickly identifies quality trends and patterns, production throughput can be increased. Actual quality data is then made readily available for Product Lifecycle Management applications to use in the next design iteration or to come up with ideas for new products.

Automation + integration = Supply chain agility and flexibility

As shown, a business process that spans from customer order through manufacturing and delivery can be done in a fully automated “lights-out” manufacturing process. This is only possible with the creation of a digital thread and the use of Industry 4.0 technologies. This ensures a single source of truth across different business functions, and helps to minimize data latency for faster and more accurate decision-making.

Without this unified platform, manual intervention is nearly always required to know your production status. In times of supply chain disruptions, decisions need to be complemented with complete data sets—because if the wrong decision is made, it can results in negative consequences throughout the supply chain. The 24x7 nature of most manufacturing operations is such that every hour of output is valuable to meet customer demand. A delayed decision due to incomplete, inconsistent, or old data can result in missed customer orders or material scrappage.

What does this all mean?

Automation alone doesn’t result in improved productivity or agility across a company’s manufacturing operations and supply chain. Integrating automation with enterprise applications does—by increasing visibility, implementing close-looped operations, and enabling data-driven decisions. The resulting increase in operational excellence and supply chain agility can lead to higher customer satisfaction and profitability.

Watch our demo series to learn how to move your supply chain forward.

Joel De Guzman

Senior Product Marketing Manager, Oracle


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