The benefits of digital transformation include:

• Improved customer experience: Digital transformation can help you better understand and meet the needs of your customers. With the use of data analytics and other digital tools, you can gather insights into customer behavior and preferences, and tailor your products and services accordingly.
• Increased efficiency and productivity: Digital transformation can automate many processes, reducing manual labor and freeing up staff to focus on higher-value tasks. This can lead to increased efficiency and productivity across your organization.
• Competitive advantage: By embracing digital technologies, you can stay ahead of your competitors and differentiate yourself in the marketplace. This can help you attract new customers and retain existing ones.
• Cost savings: Digital transformation can help you reduce costs by streamlining processes and eliminating unnecessary steps. This can lead to significant savings over time.
• Innovation: Digital transformation can open up new opportunities for innovation and growth. By embracing new technologies and ways of working, you can develop new products and services that better meet the needs of your customers.

Adopting the Right Technology

The first step in digital transformation is choosing the right technology. You’ll want to consider:

• Software: What are your current needs and how will they change over time? Will you need additional features or functionality?

• Hardware: Do you have enough computing power and storage space for all of your data, or does it need to be scaled up or down depending on usage patterns at different times of day/year/etc.? Do you have sensors to track data that you need for production insight?

• Tools: What tools do developers use to build applications on top of this platform (e.g., Creo vs. Solidworks)? How easy is it for them to integrate their code with existing systems like databases and messaging queues? Are there any security issues with using these tools – and if so, how can they be mitigated by using another tool instead (e.g., switching from MySQL database server software to Microsoft Azure).

Implementing the Digital Transformation Plan

• Develop a timeline. The first step in implementing your digital transformation plan is to develop a timeline with milestones that will help you track progress.

• Set goals and objectives for each milestone. Once you’ve established your milestones, it’s time to set goals and objectives for each one of them so that everyone involved knows exactly what needs to be done at any given time during the project.

• Track progress regularly by reviewing dashboards or reports generated from data collected during testing phases of development projects (if applicable). It’s important not only for managers but also employees on lower levels within organizations who may not have access

Monitoring and Evaluating Performance

Monitoring and measuring performance is an important part of the digital transformation process. It allows you to identify areas where you are successful, and areas that need improvement.

Monitoring can be done using a variety of tools, including:

• Data Analytics Dashboards (e.g., Thingworx Analytics)

• Real-time Data Share (e.g., Windchill, EAC Productivity Apps)

• Digital Twin Performance (e.g., Augmented Reality)

Communicating the Benefits of Digital Transformation

In order to communicate the benefits of digital transformation, it’s important to understand who your stakeholders are and what they want.

If you’re working in an organization with a large number of stakeholders (such as a government agency), then there may be multiple groups that need convincing. For example:

• The board wants to see results from their investment in IT infrastructure. They’ll likely be interested in metrics such as ROI and cost savings.

• Executives want quick wins that will help them achieve their goals, but they also need proof that this new approach will work before they can commit time and resources to implementing it throughout the organization.

• Employees want something tangible they can hold onto when explaining why this change is important for them personally (and why it matters).

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.