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Digital Transformation of Data from a Disjointed Legacy System into the Cloud

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Description

Gain insight into how the technology can help transform the traditional organisational system to become modern, productive, and cost-effective by utilising product customisations and configurations that fit the specific organisation's needs. We will show how Upchain answered the call for transforming messy data and legacy systems into a synergy of custom-tailored processes that all work on unified digital transformation. We will show how this process was implemented within ATS Automation Tooling Systems, a company that designs and builds custom factory automation systems.

Key Learnings

  • Gain insight into how Upchain can bring order to data for an organisation with dozens of legacy systems.
  • Learn how digital transformation helped organisation to move out of traditional, disjointed PLM into a modern and cloud based
  • Discover what practices you can use for utilising mechanical and electrical designs in one system.
  • Which ATS Corporation products and facilities are leveraging the Autodesk Upchain product.

Speakers

  • Andreja Schneider
    Andreja Schneider is a Product Management Engineer at Autodesk working on PDM / PLM product portfolio. She has over 11 years of experience in the Industry and works closely with Autodesk customers, partners and internal stakeholders on Upchain product consulting and development strategy. Before moving into Product manager role, she worked as BA, QA and Product Owner.
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Transcript

ANDREJA SCHNEIDER: Hello, and welcome to today's session where we are going to talk about the digital transformation of data from disjointed legacy systems into cloud. This is going to be an Upchain customer case study. My name is Andreja Schneider. I'm from Autodesk. And with me, I have Colin Henderson from ATS company.

And with that, let's move to the safe harbor statement. Please take a few moments and read through the safe harbor statement. The most important part is that this is AU content, and it is proprietary. Please do not copy, post, or distribute without the express permission.

Let's move into introduction and agenda. So as I said, my name is Andreja Schneider. I'm a product manager in Upchain within Autodesk. And with me, I have Colin Henderson. He's a manager at engineering business systems within the IT within the ATS corporation.

Let's go through summary and objectives of today's lesson. In order to scale their business, an organization consisting of dozens of legacy systems was able to digitally transform out of traditional PLM system and into a modern and cloud-based one. We are going to show you how they accomplish this with the help of Upchain. We're also going to show the processes that the organization used in order to achieve this.

Now, let's go through today's agenda. So after the introduction, we are going to talk about what company ATS was looking for. And then we are going to tell you what was achieved. Also, we are going to speak about elements included in the process. And in the end, we will show some ATS project examples. And we will finish off with the summary.

So moving into introduction. So first of all, we are going to talk about Upchain. So Upchain is a cloud-based SaaS solution for PDM, which enables delivering of data and process management capabilities that enable manufacturers to digitally transform product development and collaborate seamlessly across the value chain. It is used by engineers, by designers, by project managers, and any extended teams to ensure everyone works from a central source of truth for the product data. Some of the elements that Upchain product include are managing projects, bill of material, business processes, multi-CAD support, customizable and business-oriented workflows.

So what can you do with Upchain? With the ability to connect, our users can use design from multiple CAD tools and bring them all into one collaborative plan. With modifying, companies can have different teams all working on the same build material while keeping and tracking revisions and history, thus enabling concurrent engineering. Organizations can use adjustable and configurable processes and implement additional product revision and quality control. And with the ability to inform, system can notify the stakeholders as they are getting involved into the process.

Let us show you some of the more notable Upchain customer examples. So you can see that we have customers from different industries ranging from automotive to industrial machinery to consumer electronics and even education and fitness technology. Now, to go into details for one of our larger customers the ATS company. Colin, handing over to you.

COLIN HENDERSON: So ATS is an industry-leading automation solutions provider. And I like to say to people who ask, we make things that make things. So we make the machines that other companies use to make their product.

We've got a wide breadth of custom automation experience. We've been doing this as an organization for quite some time. So we've built up our experience here with custom repeat and the value-added products around those machines. And we service a wide breadth of industries with our machines here.

Next slide. So since our initial founding in 1978 by-- started out as a small company inside his garage. It has grown into this international automation company with 40 years of total experience. 20 countries, 60 facilities, 80 offices, and over 6,500 employees around the globe now.

ANDREJA SCHNEIDER: So what was the ATS challenge? They had their own legacy system that had a high maintenance cost. There are a company that supports many industries, so we're looking for a tool that would be flexible enough to match their many different processes adjusted for specific industry regulations. Request for change was also driven by their need to enforce the modern PLM and to improve their processes in data organizing and maintaining, all of that with a tool that can support and improve their legacy data.

So what was it is looking for? They wanted the cloud-driven solution with high-level control of systems and processes, which would support their organizational business needs. Also, it would help them reduce the dependency and costs in maintaining their own infrastructure.

The solution to their need had to be collaborative in nature and able to support their worldwide organizational units while also keeping their data secure, allowing for data to flow where needed and when needed. While keeping up with their many processes and being able to support them, the solution would also need to be able to improve the quality of legacy data while ensuring the new data comply with their regulatory data standards.

So what was achieved? Instead having the on-prem solution, which requires heavy maintenance costs, Upchain offered a hosted and externally managed solution for ATS data and processes. Options configurable processes were able to adjust ATS's specific type of business units, all that within one shareable system where data can flow back and forth with adjusted permission control level.

ATS did not need to clean up their data first in order to bring the data into the Upchain system as it would be the case with other solutions. But instead, Upchain offered for importing of legacy data as is. And when data was reused, it would be adjusted and corrected into the process. With that process, ATS was able to achieve a higher level of standardizing their data than compared to before.

What was the outcome? So having one central data system, ATS business units or divisions were able to work together more effectively in real-time across continents. Now, divisions in Europe would collaborate and contribute to the same project or assembly lines as the one in North America, giving ATS flexibility to work on even larger scale projects or even parallel lines projects with a different config settings. Their biggest programs today include assemblies that are larger than 100,000 components. Colin, would you please explain to the audience what program in your organization means and consists of?

COLIN HENDERSON: For us, a program would be a collection of projects. So a program may comprise of multiple builds of the same type of line, or it may be a collection of projects where we're building several lines working together to achieve a final product.

ANDREJA SCHNEIDER: Yeah. So showing you here just a glimpse of one of the large building material data set that we store in Upchain. And imagine the complexity of such a large bill of material, the effort it takes, the alignment of many teams and divisions to simultaneously work on bill of material of 100,000 components. And with this, we are moving into process highlights.

We would like to dive into Upchain's processes and explain the three-step process that ATS is using. First, starting with the design. Their engineering create the required design and building material data. They have the flexibility to either create the data from scratch or to reuse many legacy data, which they would use as is. Or can create new versions of and integrate into their design.

After the design is done, it is being sent for review and verification using a change request, which uses both combination of automated and manual checking processes and routes the data and build material design to the appropriate management, which is belonging to specific part of the organization. And after design is approved and released with the change request, engineers order required bill material amounts and participate in ordering process by instructing the procurement team when is expected such order arrives in the warehouse for the assembly. Let's go into more details into each of these processes.

So here, we are starting with multi-CAD support. And here, we'll be demonstrating how ATS is importing the data into the system. Also, how system recognizes the different data attributes and creates appropriate item types.

ATS is also using options item numbering and revision control schema for their users to differentiate between legacy and data changed in the system. Upchain is also offering both version control on the BOM or item level, but also on a file or CBOM level. A file may or may not be associated with an item in the BOM. And from ATS's standpoint, bill of material level has greater importance over the CBOM or the file level.

So in this video, you can see how an engineer is importing the design into the Upchain using a plugin, where Upchain can link the top assembly to a specific bill of material item created in advance under associate project. And thus enabling the import of the design directly into specific instructed project. This can be used for data organizing means or for security, where only team members can access the data.

The attributes on the files are being read and checked, and appropriate item types within the structure are being created in the system. Engineer has the means to review the data while it is being imported and data is locked for the user while they are making changes. In the plugin, user has many available information to review the data before committing the changes. And anything that is done and saved in the plugin, it is also being reflected in the web app. That's for the other engineers, engineering managers, or project managers to review.

Moment attribute and structural changes can be further done in the web app without the need to change the CBOM files. New material structures are fully reusable between the projects. And because of revision control and various information, it also offers history information tracking.

Now, moving into adjustable business processes. So after the design has been finished, it is sent to change request process for approval. ATS change request workflow uses many level of controls and checks for appropriate attributes of submitted items based on business unit association, project association, CAD data association, and many more. In case any of the data being checked by the workflow is not correct, it will stop and create a task with requested detail, also for the appropriate person to correct the data.

When all checks pass and data is conforming by the business rules set in the workflow, appropriated designated persons are notified about the design changes and requested to approve the design. After this is approved, the system is making the necessary data changes in order to release the design and create additional metadata. For example, like populating driving attributes and curly codes or creating translations.

Now, just for comparison on complexity of ATS change requests workflow, here's an Upchain's out-of-the-box workflow with just 10 steps. It encompasses the basic processes for approval and release of the BOM. And now, this is the ATS change request workflow, which contains over 100 steps, out of which some need to go through several iterations in case design and data need to be corrected.

Going back to Upchain demo within the web app. Here, we are showing that after design changes have been made, an engineer triggers the change request process or the CR. The CR workflow makes the necessary data and attribute checks. And in case anything is missing or not conforming to the custom rule set, the system creates a task for responsible person and can also send a notification email about the work that is required. Task is filled with details that need to be corrected or with instructions for the reviewer to check the submitted data set before the approval.

Approver can review the data by downloading it right from the web. And if necessary, reject the design. The engineer would update the design data after receiving a task for it and submit to a review process, all that within the same CR workflow process.

After the approval has been given, data is updated and marked as released, together with all supporting metadata. Such release the design is now locked for further editing. And if required, an engineer would create a new revision of an item to start next iteration of the design.

After release is done, engineer would proceed with requisition process, which contains mechanisms that prevent over-ordering of assembly components. All that with a goal to minimize the ordering expense cost and scheduling mechanisms which signal to procurement department when it's required that particular component arrives into the warehouse. Thus enabling component delivered at the right time so that assembling process would not be halted until a particular component arrives.

After required components have been identified, the requisition is being reviewed and approved by required management team based on the total cost basis. And after approval was given, bill of material and requisition data is being extracted out of the option and sent to ERP system over an API connector. This short example of a requisition order we are showing how a release assembly is being ordered over several requisition processes.

Upchain is checking the assembly bill of material quantities and uses that information to calculate the maximum allowed amount for order of selected components within a requisition, thus preventing over-orders, which, in case if this mechanism would not exist, could cause for additional cost for the company. After workflow is initiated, a responsible approver will get this task for review, also with the work instruction detail. And after the approval, the system records the previous ordered bill of material quantities. So when a new requisition is initiated, previous orders are taken into account.

At that time, previous maximum ordered quantities can only be returned and only if needed, and other not yet ordered or fully ordered components can be requisitioned. After each requisition, information about the order is transmitted to ATS's ERP system over APIs. The Upchain system stores the information about previous requisition, as well as previous change requests if this information is ever needed for a review.

In this last part of Upchain's three-step process that ATS is using, we are now moving into next section, which will show us examples of ATS products and facilities that they are leveraging Upchain system. Colin, moving to you.

COLIN HENDERSON: So I just wanted to highlight a couple of our larger business segments that are making use of Upchain here, life sciences being one of those. And we service several technologies there, basically in the business of helping people. And we've built machines that produce products for medical devices, diagnostic, pharmaceutical, and pharmacies and laboratories.

One of our other major segments here would be the industrial automation. And they serve a wide breadth of different types of industries there as well. One of the more notable ones was probably the electric vehicle or EV mobility automation. I highlight that one just because the amount of activity lately in that area, but also nuclear automation, speciality automation. So special businesses and consumer products fit in this business segment. Next slide.

I just want to highlight that EV or electric vehicle area. This is a point case that really was enabled by Upchain, where we've added on several manufacturing facilities just to support this program running through. And this program runs across I can't count how many different business units are contributing to both the engineering and manufacturing of these machines.

And these are some of our larger bills of materials that are being built by users across the globe. And this is enabled by our Upchain implementation here, where all these users are able to interact and see the contributions by others. And then produce that production successfully to support our customers.

ANDREJA SCHNEIDER: Thank you, Colin. And with this, we move into summary. So today, we've learned about Upchain capabilities, and how ATS, a company with dozens of legacy systems, were looking for a tool that would enable them to transform digitally. Upchain was able to adapt their many processes and support their organization to scale by providing means to keep the data in one central system, which addresses their data gaps and fixes them. We also heard of three-step process that ATS is using to ensure their data is organized and standardized based on required business parameters and also secure. Thank you for listening.

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We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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