What Are Smart Operations?

Expect unprecedented changes in manufacturing facilities worldwide in the next five years. Facing competitive pressures and labor shortages, manufacturers will automate even more of their operations and develop radically new product lines and go-to-market approaches. The keys to this progress are manufacturers’ abilities to

• connect real-time operational data with business data.
• apply AI-based data analytics to derive insights and make recommendations.
• drive greater automation across supply chains and manufacturing.
• empower employees with real-time insights for making intelligent and timely execution decisions.

Tomorrow’s factory will combine data from connected equipment, the workforce, and the supply chain to deliver real-time recommendations, adjust production without human intervention, and free up talent for more high-value work.

Welcome to smart operations.

What Are Smart Operations?

Smart operations combine a manufacturer’s information technology (IT) and operational technology (OT) with artificial intelligence (AI), creating a continuous feedback loop that can help improve operations.

OT data from factory production lines, specialized equipment, and Internet of Things (IoT) sensors mixes with IT data from manufacturing execution systems (MES), enterprise asset management (EAM) systems, and applications for finance, HR, sales, marketing, and the supply chain. The combined data is analyzed using AI, and the resulting insights are fed back into systems that adjust operations automatically. This continuous feedback loop injects automation into the production process, helping boost efficiency and drive continuous improvement.

Key Takeaways

• Smart operations break down the divide between the OT systems that run a manufacturer’s factories and production lines and the IT systems that run the rest of the business.
• Data from across the company is combined and analyzed using AI-based analytics.
• Smart operations can also automate low-level tasks, such as summarizing repair work, freeing employees to perform higher-value tasks.
• This level of automated operations is possible only by applying AI-based analytics to unified data.

Smart Operations Explained

In most manufacturing companies, IT and OT are disconnected from each other. IT typically consists of the software and hardware used to run the business and secure its data for finance, procurement, sales, marketing, HR, MES, and the supply chain. OT typically includes the systems and machines that run factories and production lines: supervisory control and data acquisition (SCADA) systems, programmable logic controllers (PLCs), robots, digital twins, sensors, and IoT systems.

Smart operations bridge the divide between IT and OT. When data about machines, parts, production lines, raw materials, and finished goods combines with data from finance, procurement, the supply chain, and other business systems, manufacturing companies can identify and mitigate production bottlenecks, alert managers to potential machine failures, and use sensor data to improve the performance of parts and finished products. For example, companies that supply component parts to automakers can collect sensor data from their products to understand how they’re performing in a real-world setting.

How Do Smart Operations Work?

Smart operations begin with creating a digital twin, which is a virtual representation of the factory production line displayed on workstation monitors or mobile devices. To create the digital twin, sensors are attached to the factory equipment used to assemble products—for example, mills, welding stations, lathes, and robotic arms. Sensors might also be attached to the finished product as well as to the components that go into making the products. The digital twin collects information from these sensors—data such as the revolutions per minute, temperatures, throughput, and stability of machines—and displays it on a “visual explorer,” giving employees and supervisors a bird’s-eye view of the factory floor. The visual explorer alerts employees to mechanical problems, such as a wobbling lathe or a robotic arm that’s moving outside of set parameters.

These concepts are familiar to companies that have adopted Industry 4.0 practices, including smart manufacturing and smart factories, but smart operations take things further.

In smart operations, AI takes information (contained in OT systems) from the smart factory, analyzes it, and sends alerts back to the IT systems that run the business. These alerts, in turn, can automatically trigger more complicated tasks that, without AI, would require human intervention. Examples include autonomous production adjustments or HR tasks, such as ensuring that technicians and operators have the proper certifications to perform the work assigned to them.

Smart operations create an autonomous feedback loop of “sense, respond, decide, and do,” which moves manufacturing toward lights-out operations. Collecting, combining, and interpreting operational data to execute complex tasks is possible only with the power of AI-based analytics on a unified cloud platform.

Characteristics of Smart Operations

Smart operations include a single user interface that provides everything operators need to execute their work. This setup can even replace traditional manufacturing execution systems, which are often point solutions that don’t integrate well with other enterprise systems.

Smart operations have four key characteristics.

• Connected: From design to the factory floor, smart operations require a single “digital thread” that weaves together data from different environments and stages in the lifecycle of a manufactured product. This connectivity gives employees and managers visibility into manufacturing operations as they happen in the physical world.
• Unified: In smart operations, the data for a manufacturing task (such as a work order) is linked with the business transaction that generated it (for example, a customer order). Smart operations use a single data model to unify business and production data, helping ensure that orders are built to the right specifications to satisfy customer demand.
• Intelligent: Smart operations use AI-based data analytics to deliver unprecedented insights in areas such as quality assurance and control, the performance of the production line, the performance of the final products, and the availability of assets in the field (such as a leased airplane or communications tower).
• Automated: With smart operations, changes driven from upstream (such as changed order priorities or production schedules) can be rapidly implemented on the factory floor. Conversely, issues such as faulty or failing equipment can be identified quickly and used to influence upstream business processes (such as planning and maintenance), boosting productivity and helping employees make smarter decisions.

Business Benefits of Smart Operations

Manufacturers stand to gain a competitive edge by giving workers the right data and insights at the right time. Smart operations can make employees more engaged, letting them focus on improvements that create more value for the business. The benefits of smart operations include

• Improved overall operational performance. The continuous monitoring and feedback loop of smart operations help manufacturers increase productivity, enhance quality, expand production visibility, and improve factory output.
• Improved employee recruitment and retention. Most people want to join and stay with companies where they can make a difference. By automating low-level tasks, smart operations free employees to help solve the bigger problems of the business, so they’re more engaged.
• More resilient supply chains. By applying AI-based analytics to OT and IT data, supply chain managers can receive automatic alerts to potential work stoppages and respond by quickly changing plans, suppliers, or logistics.
• Lower risks and costs. Adjusting production based on supply and demand signals remains a challenge for many manufacturers. At the same time, rising material, labor, and overhead costs make it difficult to maintain profit margins. Smart operations can reduce demand risk because supply chain managers get faster alerts to potential disruptions and can respond quickly to make alternative arrangements. Smart operations can reduce costs (and thus increase profit margins) through higher levels of automation.
• Faster growth. Smart operations help maximize capacity so that the manufacturer can produce more products, faster, to meet demand as it grows. For example, if a manufacturer wants to support a new business model, such as adding customization services to existing products, smart operations can provide the automation needed to produce customized orders more quickly and accurately and to predict when the product will require maintenance.
• Embedded sustainability. The continuous feedback loop of smart operations helps the company meet its sustainability targets and take corrective action quickly when it’s at risk of missing goals. Manufacturers’ sustainability goals include reducing consumption of energy and natural resources, reducing the negative environmental impact of their products, and improving employee and product safety.

Challenges of Smart Operations

The biggest challenge to smart operations is that a manufacturer’s IT and OT are often managed by different departments, each with its own priorities. Those departments might even run independent networks and procurement and budgeting processes. Other challenges include

• Legacy applications, usually running on premises, that invariably were highly customized but are now obsolete, requiring changes to the underlying code. The technical effort required to make those changes slows down the pace of innovation.
• Manufacturers’ struggle to connect their MES to the digital thread described above. Often, they rely on point solutions chosen independently by different groups across the organization. This proliferation of systems creates more complexity and makes it more difficult to streamline and automate operations.
• Solutions working in isolation from one another. For example, product lifecycle management, where most of the product design and development takes place, isn’t well connected to the MES, slowing down improvements to the final product.
• Maintenance that runs independently of operations, making scheduling inefficient and reducing uptime for assets sold or leased to customers (such as construction equipment).
• IT and OT systems that use complicated, inconsistent user interfaces designed to feed the system rather than meet user needs. They get in employees’ way instead of helping them do their jobs better and faster.

Future of Smart Operations

The concepts of smart operations can be applied outside of manufacturing. The closely related field of maintenance, for example, can benefit from the same capabilities for predicting when machines might fail and dispatching repair crews to prevent it. The data fed from assets in the field, such as cell phone towers and jet engines, can be used to improve these assets and increase uptime.

Other product-centric industries can also apply smart operations ideas to their supply chains. In healthcare, for example, applying RFID tags to medical supplies and using automatic replenishment and robotic picking can deliver significant labor and cost savings while helping improve patient outcomes. Or a power company can use a digital twin to provide an exploded view of all the component parts inside a malfunctioning transformer, see precisely which part is failing, dispatch a repair crew, and even generate a purchase order for replacement parts.

Embrace a Smarter Future with Oracle

Oracle offers an integrated suite of cloud-based manufacturing applications. Oracle Smart Operations provides a new set of capabilities built into Oracle Cloud Supply Chain & Manufacturing. The new functionality helps increase operational performance and helps the workforce make intelligent, timely execution decisions. It combines real-time operational data with business data and advanced analytics for delivering recommendations, simplifying processes, and increasing automation across the supply chain and manufacturing.

Oracle’s suite of cloud applications share a single data model, providing the unified architecture needed to connect IT and OT. Oracle is also adding generative AI capabilities to its portfolio of cloud applications. Oracle solutions for industrial manufacturing, coupled with Oracle’s data analytics solution, give manufacturing companies deep insights, automatic alerts, high levels of process automation, and an intuitive user interface designed to make workers’ jobs easier.

Smart Operations FAQs

What is a smart operation?
A smart operation makes extensive use of operational and business data to alert employees to situations that need their attention and to automate tasks that previously would have required human intervention. It’s an autonomous feedback loop of sense, respond, decide, and do.

What are the five essentials of intelligent operations?
The five essentials are a digital thread that connects information technology (IT) and operational technology (OT); operator workstations that alert employees to potential problems and recommend improvements; a user interface that’s intuitive for employees; a unified set of cloud technologies on a single data model; and AI-based analytics, overlaid on the connected IT and OT data.

What is smart operations management?
Smart operations management is the field of managing and improving smart operations, with the goal of automating complex tasks that previously would have needed human intervention. It’s a move toward autonomous, “lights out” manufacturing operations.

What is an example of smart manufacturing?
An example of smart manufacturing is a production line that uses sensors attached to the equipment, machines, and components used to make the final product. These sensors feed data back to production line workers—for example, alerting them to potential problems on the line (like a machine about to fail).

Is Industry 4.0 the same as smart manufacturing?
No. Smart manufacturing is one component of Industry 4.0. Other components include smart maintenance, intelligent supply chain management, connected logistics, drones, robotics, and cybersecurity.