Pegasystems

Digitization means disruptive mega-trends in connectivity, social, Internet of Things (IoT), big data analytics, cloud and mobility. The transformational aspect of digital technologies is paving the way for digital innovations across industries. In the manufacturing arena, a number of key trends are ushering in a new digital transformation. First, due to digitization trends, the pace of change for products and services is ratcheting up exponentially. Second, today’s economy means “doing more with less.” Third, IT is challenged by disruptive technologies and more tech-savvy business stakeholders. And finally, IoT is transforming the entire end[1]to-end manufacturing value stream. Two after[1]market services are particularly transformed through digitization: device directed warranty and digital prescriptive maintenance, and both are enabled through the digital Process of Everything.

The impact of the alignment of the cyber world with physical connected devices should not be underestimated. Devices are generating enormous amounts of information that is mined, analyzed and acted upon. With increasingly connected devices, traditional manufacturing models no longer apply. Historically, physical things and software that makes up the realm of IT have been siloed. Embedded software solutions with physical devices and the maintenance and control of physical things fall into the realm of operational technology (OT). These physical and virtual worlds are coalescing in the new digital enterprise.

The value stream is a model of the various stages assigned to business owners, and a dynamic case is ideal for digitizing the value stream. Big data analytics, business rules and intelligent integration are all part of dynamic case management (DCM). The anatomy of a case is illustrated below via people, connected things and robots with machine learning capabilities. A case orchestrates multiple tasks, and each stage is achieved by the completion of digitized processes. Cases are dynamic. Business rules, predictive and self-learning analytics constitute the nervous system – the intelligence of things, digitized decisions and workers drive the case to resolution.

It is truly a Process of Everything–people, things and big data (which is quickly becoming “thing” data).

•Things as Participants in Processes within Dynamic Cases: humans, things and applications orchestrated within processes mapped to DCM stages

•Dynamic Cases Instantiated from Thing events: where a sensed event instantiates a case

•Complex event correlation and Big Data analytics to instantiate cases: real-time analysis to correlate events or predictive modeling to discover and operationalize models within DCM

Business rules, predictive models and decision management are leveraged within automated dynamic cases, with IoT connectivity. The Process of Everything is also transforming after-market services.

Device Directed Warranty (DDW)

Historically, warranty management has been relegated to a back office function challenged by:

• Manual and non-value added processes

• High cost of compliance and reporting

• Customer dissatisfaction with poor claims handling

• Smart devices flooding the system with data – and the obligation to react

The Process of Everything enables digital transformation to resolve these paint points via increased connectivity and efficiency. •IoT Diagnostics: Things will have on-board central processing unit and execution capabilities.

Automatic Updates of On-board Device Software: Edge devices have sophisticated software that can be updated remotely by the manufacturer.

Automatic Sense and Data from Edge Devices: A manufacturer might gather data from the device or ping it for measurements and analysis.

Automatic Control for Maintenance: Devices can also be controlled remotely or through on board decisioning software.

• IoT Supply Chain and Parts Return: The device and returns of defective devices can be monitored from the supplier to the manufacturer to the customer.

• IoT Repair or Parts Validation: Once the repair is completed, the manufacturer can validate the fix and warranty coverage.

DDW is an important stage in the overall connectivity of manufacturers to their products. The relationship continues in this alignment of the digital and physical product era, especially in proactive maintenance.

Digital Prescriptive Maintenance

Total productive maintenance (TPM) focuses on improving overall equipment effectiveness (OEE). The calculation of OEE is performance X availability X quality. The objective is to create an environment that engages employees in preventing costly equipment breakdowns. Business rules and big data analytics are important aspects of maintenance optimization that spans “descriptive,” “preventive,” “predictive” and most importantly “prescriptive.” Digital prescriptive maintenance (DPM) means:

• Total productive maintenance

• Descriptive, preventive and predictive analytics of equipment data for maintenance

• Automated processes with IoT sensors and DCM: Process of Everything

The evolution from traditional TPM is a dramatic shift from minimizing down-time to a much more proactive approach. With DPM, machines predict potential failures and autonomously trigger maintenance – with minimal human intervention. DCM automatically creates a maintenance case with tasks assigned to things or people. Maintenance is done remotely by software or if a technician is dispatched, they arrive with advanced information and the right parts. The case data is mined, and the root causes are analyzed to prioritize the next best actions and the most likely solution. Machines become self-learning and over time can take care of themselves to reduce manual efforts.

Digital Transformation of Manufacturing

The impact of IoT through Process of Everything extends to the entire end-to-end value stream of manufacturing. For example, a global manufacturer is using DCM with decisioning and digitized processes to complement their enterprise resource planning system and improve their product quality. Data is logged at every stage throughout the process, and defects are correlated with the series of events and machine data, such as temperature, humidity and speed to determine root causes. A case is created to monitor the actions required to correct the defect and prevent it from happening again. This closed[1]loop feedback allows operators to make real-time adjustments to improve first-pass yields and reduce scrap.

Embedded sensors, software, controllers and connectivity are creating a digital revolution in manufacturing and aftermarket services. Breakthroughs in networking, edge computing, cloud technology, energy efficiency and miniaturization are converging to create low-cost processing power and data storage everywhere. Computers in machines, gadgets and wearable devices are streaming data about their operations and conditions. Things will soon generate more data than people or applications. Translating that data into insights and intelligent decisions is the key to effective analytics. The intelligent decisions need a digitized process context and orchestration of tasks for the actions executed by people, enterprise applications, supply chain partners and increasingly smart things or devices. The next industrial revolution is already here.