In today’s world, it’s not uncommon for companies to be rich in data but poor in insights. Despite having access to a wealth of information, organizations struggle to properly analyze performance and drive transformational improvements. This is where ThingWorx Digital Performance Management (DPM) steps in to bridge the gap.

This week in your factory, you’ve applied maximum effort, pouring countless hours into perfecting your product. As the work week ends, a feeling of slight disappointment remains.

Could you have accomplished more? Where did it go awry? You may not be able to find the answers on your own, leaving your factory inefficient and operating below its full potential.

If this is you, look no further. With the capabilities of Thingworx Digital Performance Management, you will unleash an untapped potential of data and boost your manufacturing processes.

What is Digital Performance Management?

ThingWorx Digital Performance Management (DPM) is a cutting-edge solution designed to help organizations identify, prioritize, and improve production issues.

By capturing lost production hours and their causes, DPM indicates where to focus for the most critical impact. Also, it optimizes the finite time available, allowing organizations to reclaim lost hours and increase effective time by 20% or more. Thus, directly impacting the bottom line.

How Does DPM Work?

Consider a manufacturing facility that can produce one unit per hour. In a week with 88 hours worked, the facility manages to manufacture only 44 units. Let’s say 12 hours are lost through planned downtime and 14 hours are lost due to changeovers.

That leaves about 18 hours unaccounted for. Where did those come from? With ThingWorx DPM, you can quickly identify issues, and why they happened, and then take appropriate actions to fix them.

Moreover, DPM calculates and analyzes discrepancies, providing valuable insights to improve productivity. DPM is a comprehensive toolset that propels organizations towards peak performance by tracking performance, conducting in-depth analysis, planning, and validating improvements.

The Production Dashboard

One feature included with DPM is the Production Dashboard. The visual dashboard is a crucial tool for supervising shift performance and gathering vital data to inform reporting and analysis. It is designed for supervisors and line managers to track productivity across various production lines.

Some key features of the Production Dashboard include:

• Provides insights into shift progress at the production block level

• Allows for automated and manual data entry, including reason codes to capture all losses

• And offers a simplified interface to minimize disruption

Bottleneck Analysis

The Bottleneck Analysis tool is designed to automatically detect and monitor the most significant bottlenecks in your factory, providing valuable analysis and insights into OEE and OLE.

One of the challenges that customers face is a lack of visibility into bottlenecks, which leads to a disconnect between continuous improvement efforts and their impact on the business. However, bottlenecks are often dynamic and complex.

To address these challenges, DPM offers key capabilities to help identify and resolve:

• Automatically identifying and tracking bottlenecks.

• Systematic identification of the top constraints, which can significantly increase factory efficiency by 5-20%.

• Management of the dynamic nature of competing bottlenecks.

Overall, DPM works relentlessly, making up for lost time by tracing the root cause of issues and providing precise remedies to ensure smooth and efficient functionality. Consider DPM an invaluable employee, working tirelessly around the clock without additional overtime costs!

Accelerate Problem Solving with DPM

DPM’s capabilities extend beyond surface-level analysis. By combining Pareto analysis and time loss analytics, DPM users can uncover and address a significant percentage of production problems.

Additionally, with the further integration of AI and machine learning, DPM streamlines the identification of patterns in data, resulting in faster problem-solving and decision-making.

For instance, a DPM user noticed quality losses between 3 p.m. and 4 p.m. Thanks to DPM’s automated analysis, the manufacturing team quickly determined that the issue was caused by a glare from the sunset, making the inspection camera unreliable.

All in all, DPM helped accelerate the problem-solving process saving valuable time and resources.

Reap the Benefits

Digital Performance Management is as remarkable as it sounds. DPM holds the secret to your production improvements and is ready to share them with you. Discover the plethora of benefits that are tied to DPM:

• Standardized Measurement: DPM provides a consistent and standardized approach to measure losses, ensuring accurate evaluation of bottlenecks, and their impact on performance.

• Efficient Root Cause Analysis: Leveraging AI technology, DPM identifies the root causes of bottlenecks and facilitates their permanent resolution, eliminating recurring issues.

• Automated Problem Identification: DPM’s powerful AI algorithms automate the process of surfacing common issues, exponentially reducing the time spent on problem-solving.

• Real-time Insights: What once took months to identify critical insights now becomes easily accessible through DPM’s intuitive interface, providing teams with immediate access to actionable insights.

Get Started with DPM Today!

In conclusion, if you want to revolutionize your performance management and take your organization to new heights, it’s time to embrace Digital Performance Management.

Remember, in today’s fast-paced world, those who leverage technology to gain insights and make data-driven decisions are the ones who thrive.

Are you ready to unlock the true potential of your organization with Digital Performance Management? Talk with an expert now to take your first steps toward success.

They say a picture is worth a thousand words, so here’s a hypothetical situation to paint the story ‘how real-time information and predictive analytics unlock value.’

To start, imagine a fully functioning assembly line with a robot, a pneumatic system, a series of conveyors, and a vision system.

Let’s pretend the supply station in the back is bringing in our raw materials. The robot is assembling those materials with precision. The resulting assemblies are then passed on to the quality station, and the vision system inspects each of those assemblies to ensure proper alignment of the parts.

This is a pretty generic operation, but it can show how unified real-time information and predictive analytics unlock value.

Now imagine yourself as a maintenance engineer, who wants to check the status of your asset pool.

Using software, such as ThingWorx Navigate by PTC for example, you launch a role-based maintenance application. All of a sudden you see a complete list of your assets with real-time performance stats and relevant alerts or notifications. You also have a complete list of all your outstanding maintenance work orders.

From here, you have the ability to drill into any of your assets, but you start with the quality station. You immediately see the key characteristics of the station.  You see that speed vibration and temperature are all operating within their specified range. You could also see notifications of any warnings, malfunctions, or potential future problems.

Next, you use your device to take a look at the pneumatic system.  The pneumatic system also looks fine. Both pressure and flow are operating within the specified range, and there are no outstanding maintenance tickets or work order notifications on your screen.

Now, let’s consider a situation where there was a leak in the pneumatic system.  Let’s say a loose fitting was releasing pressure, a fairly common problem in pneumatic systems. Now, rather than looking fine,  your device displays flow readings outside of the designated operating range. Furthermore, an alert has automatically been sent to notify you that a system has an error. The overall status indicator on your screen has now switched from green to orange – operational, but not optimal.

Your software solution’s machine learning is now predicting that this air leak, if not repaired, will result in a pneumatic gate failure in approximately 10 day’s time. The good news for you is the system has already issued you a maintenance work order to address the problem before asset failure and unplanned downtime.

This scenario is made possible by a system equipped with primary and secondary sensors, and a complete Industrial Internet of Things (IIoT) solution that can turn raw machine data into valuable information.

For example, your pneumatic system has an airflow sensor, as well as a pressure sensor.  The conveyor systems are equipped with motor temperature sensors and vibration sensors.

In addition to the sensors, the rest of the assets on your line are controlled by typical PLCs, which are connected to software such as ThingWorx and Kepware.

You have also used your software to integrate manufacturing floor systems with real-time IT applications, asset maintenance tools, and ERP systems. This provides you with a real-time alignment of your IT and OT systems.

Now, all of your systems are throwing data out at a staggering 800 data points per second.

Your software’s machine learning then uses that real-time streaming data to establish a baseline of normal operating conditions. This way it can immediately connect and broadcast any anomalies that occur. It uses these anomalies, in conjunction with its prediction capabilities to notify you of future problems, just as in the case of the pneumatic failure.

Now that you have an understanding of what is happening under the hood, let’s take a look at how all this comes together to enable real-time operational intelligence.

Pretend you are a production manager. Using software like ThingWorx Navigate and Kepware you have complete visibility into all of your factory operations. You can see all of your work orders, lines, and all of their critical KPI’s.

On your device, you notice an orange status indicator on line one (that was created from the air leak earlier). Once that air leak has been repaired, everything returns back to normal, just as you would expect.

Let’s explore one more hypothetical situation. Consider yourself to be an operator. In this case, you have just been assigned a new order for a thousand units that need to be delivered and expedited for an end-of-day delivery.

You’re notified of the order and in this smart connected scenario you, as an operator have a single portal from which you can see and execute all of your work. Through a single pane of glass, you now have access to your business systems information and your operational data including the KPIs from your line.

On your device, you also have up-to-the-minute visibility of the OEE (Overall Equipment Effectiveness). You see real-time data measurements of your manufacturing operation’s availability, quality, and performance.

Let’s see how some of these metrics might change if we go ahead and speed up the line to accelerate the current order, in order to make room for that expedited order.

To do that you switch the line speed from level one to level two. What you see in seconds on your device is that line speed has increased, and your assemblies are still passing the quality check.

Within a couple of minutes and a few additional cycles, on your device, you see both your performance and OEE trending upwards.

As an operator, you now are assured that you are going to meet your end-of-the-day deadline.

Using these hypothetical situations, together we have painted a picture demonstrating how you can connect disparate assets from different vendors, to provide real-time information.

You’ve also seen how you can leverage role-based applications that combine business systems information and operational data to empower your workforce with real-time actionable intelligence.

By integrating machine-learning capabilities you brought a whole new level of predictive intelligence to your factory floor, identified problems, and resolved issues with minimal impact on operational performance.

This is exactly how real-time information and predictive analytics can unlock value for your organization.

Our Product Development System Assessment will help you start your digital transformation journey

Download Brochure

Modernized service strategies combine enterprise IT, ‘smart’ technology, and information.

Manufactures are expected to be more demand oriented, data driven, and technologically focused. This means focusing on the customer, using the data collected from many different areas, and digitally executing strategies using platform technologies.

Many companies today are focusing on the current stage of achieving field service excellence. This tends to be an easier, stand-alone area to focus on as it incorporates vast amounts of technology available to help and support them.

The next stage deals with moving towards connected service platforms which oftentimes involve an integration of smart, connected products. This is when companies will start to deal with how to capture data, leverage the insights, and turn it into actionable results for various stakeholders throughout the organization.

The last stage deals with achieving servitization optimization. Servitization is an important concept because it holds the potential to transform how products are delivered and monetized. This is really the movement towards product service systems and products-in-use value.

Ultimately, providing access to product and parts information is a crucial step in on the path to successful profitable growth.

Technology is fueling service transformation for many organizations.

For instance, here’s how ‘service’ has begun to transform with the help of new technologies:

• Cloud technologies have enabled greater access to service parts visibility and information.
• Mobile technology has put information in the hands of service technicians, at the right time.
• Big data analytics now capture asset and product information, enabling enhanced service quality with better first-time fix rates.
• And social technology has allowed engineers, service, and customer support to collaborate.

These cloud, mobile, social, and big data analytics technologies have enabled manufacturers to transition from systems to service, from information to innovation.

Our team is prepared to help you achieve field service excellence. Our Product Development Information Services team is experienced in the architecture, implementation and support of a technology portfolio making service excellence a reality for many of our customers.