Description
Key Learnings
- Learn how to identify similar pain points within your organization.
- Learn how to identify areas of improvement within your organization and relate the solution to your own ecosystem.
- Discover the benefits that a connected data workflow brings to the shop floor.
- Become familiar with the tools that would be used and how they would easily interoperate.
Speaker
- LELuke EdwardsLuke Edwards joined Delcam in 2008. Following the Autodesk acquisition of Delcam in 2014 he is now the Consulting Services Manager for MAKE projects in EMEA within Autodesk's Enterprise Customer Success team. Helping Autodesk's largest manufacturing customers to realise the potential digital manufacturing. Whether this is better data management, process engineering or process automation. His team work with customers to plan and deliver their digital transformation journey. Improving data storage and traceability for manufacturing data has allowed him to help customers be up to 40% more efficient with their time and reduce scrap rate to zero! Creating software applications to automate customers' data and machine interaction workflows, allows them to simplify, standardise and improve their most complex and repetitive processes. Also working to help the partners and smaller customers around the world to create their own automation solutions. Aiming to provide them the tools that they need to allow their best engineers to make better use of their time and keep their business driving forwards.
LUKE EDWARDS: Hi, there, and welcome to my industry talk, where I'll be looking at digital transformation in the assembly and manufacturing process. First of all, let me tell you a little bit about myself. I'm from Birmingham, in the middle of the UK, and my technical background is software development.
And I've worked in a few different industries, firstly, in the development of embedded control software for aircraft. This included working on software for engine controllers for aircraft, controlling fuel flow actuator positions, things like that. I also later worked on a battery charger for the F-35 Lightning II aircraft.
I then changed industries to work at a software company as a technical applications engineer creating customizations and workflows to help customers make better use of their software products. We help customers design their software and systems models, giving them a digital twin of their design and implementation of their product control systems. I later moved into the world of manufacturing to work in professional services for Delcam, who were later acquired by Autodesk.
And for the past 15 years, I've worked to provide services to help customers improve their manufacturing processes through automation, whether that's been small applications that shorten repetitive tasks, or lights-out manufacturing plants where custom parts are machined with little to no human involvement. During that time, I've worked with a variety of different customers in industries from hobbyist to healthcare to aerospace, doing projects that automate and optimize the creation of things like dental restorations, customized flip-flops, chocolate lollipops of people's heads. I've also helped to automate the machining of parts for the F-35 Lightning II aircraft.
I now lead a team of manufacturing engineers within Europe, who work with our named account customers on their biggest manufacturing problems. And in recent years, we've been working with customers more around their data management problems, and looking at how we can improve not only their production issues, but also their data issues. We do this via a mix of advice and best-practice guidance, process definition as well as the development of applications and utilities that customers use as a backbone in their digital processes.
So let's set some expectations and summarize what we're going to look at. I aim to take you through an outline of why we look to move to digital transformation and what digital manufacturing is. We'll look at some common industry pain points that you may recognize in your business.
We'll look at how to start untangling the current process and where digital transformation can add the most value. We'll then dig into solutions to the pains and problems, and I'll share some success stories of where I've seen digital transformation bring great value. We'll conclude with looking at what you might do to start your digital transformation journey.
So let's start with looking at why we might go through transformation, what holds us back from starting, and how we find the motivation to make the first step. Firstly, we've just been through a huge amount of change as a civilization. Nobody was ready for it, but we had to adapt.
Businesses had to change just to keep things running. As humans, we generally don't like change or risk. As a general rule, it scares us.
Consistency, safety-- they're essential parts of feeling stable in life. But during COVID and lockdowns, we were forced to adapt, whether it was balancing work at home while schooling our kids or working out how to have two people collaborate closely together while still being 2 meters apart.
But many companies were able to adapt. Yes, it was difficult. Yes, there were issues.
And maybe we aren't all better for it in all areas. I still bear the scars of home schooling. But we realize now that we can make change happen.
Overnight, companies who never thought working from home for their employees was a possibility had to adapt and work out how to move to digital solutions. Companies had to work out how to get employees to communicate efficiently and collaborate effectively using asynchronous and remote working methods.
One example I will share is that during the last couple of years, I've seen a simple, yet effective change in the way the group I work in have been making more use of OneDrive and doing real-time collaboration within office applications. Previously, we were content with sending copies of documents back and forth via email, always confused about which was the latest version.
Yes, it's digital, but it isn't optimal. Now, we use OneDrive and collaborate real time in Word and Excel. There's one single live version.
And when we want to draw a line in the sand, that version is exported to PDF. It's a simple change, but we no longer spend time wondering who has the latest file. And collaboration happens in context within the documents.
So we know we can change, but what stops us? We're busy getting on with work and making money. Why would we bother? Sure, we recognize there's some inefficiencies, but they can't be that bad. We're still making a profit.
We often have the preconception it's expensive to change. Can we take the return on investment risk? How do we even calculate the ROI and what the time scale for payback is?
We have data everywhere-- network drives, people's computers, paper copies, multiple discrete IT systems. Where do we even start? What are our motivators and how do we justify taking that first step?
What happens if we don't change? I'm constantly reminded every time I jump on my bike by the people that specialized-- innovate or die. If you don't move forward, you're moving backwards. We've all heard these statements.
What happens if we do change? The State of Design and Make Report that was released earlier this year has seen Autodesk partner with Ipsos to survey over 2,500 industry leaders, futurists, and experts. That report tells us that design and manufacturing customers know that the four main reasons for change are around cost reduction, innovation and time to market, decision making, and ultimately, happier customers. I'll come on to some real-world examples and values that I've seen in these areas later.
So what are our motivators for change? How do we justify and make that first step? What are the pains that we have now that we should focus on and gather around as to why we should change? What comes to your mind when I talk about production pains? What are the main causes of those pains?
Three of the main things that people talk to me about are communication-- how often we communicate with each other and how we communicate compared to what is optimal. If there's too much communication we have difficulties. We're having to discuss things that shouldn't need to be discussed. We ask clarifying questions that should be known, documented, and referenceable. Endless Zoom and team meetings, many wasted hours, and employees that become single points of failure.
If there's not enough communication, there's a lack of discussion around things. People become afraid to ask questions. There's unknown unknowns, and the wrong things, so nothing is documented. If that hit-by-a-bus event actually happened, how would you recover from that?
What about traceability? Are we working on the right data? Is it the latest data? Did we use the latest source information when we created our information?
Can you be sure that when you hit Cycle Start on that machine and produce that part, that you're producing to the current customer specification? How do you something didn't change upstream or that if it did, you rolled it down correctly and nothing was missed? Are you sure you aren't about to spend hours machining something that will ultimately be scrapped?
If you are producing a wiring harness, can you be sure that when you put it together that the harness is made to the correct standard to go into the vehicle? What will it cost if you have to rework that if it isn't?
What about collaboration? I hear, yeah, I know Dave. I went to his kid's christening. We often speak at the coffee station, but he works in design and I work in production.
We've all heard of it-- the dreaded data silo, the idea that we're disconnected from our colleagues by departments. That could be because they use one tool set and you use another, or they store their data in one area on the network and you store yours in another. Or your processes define that when Dave finishes his work, he passes it to you via email, with gated times to discuss it in monthly review meetings. Collaboration becomes an over-the-wall mentality, with interaction only happening at discrete moments.
And all of this at what cost-- time and money? Two customers in the last couple of months told me exactly the same number. Their front-line engineers are losing up to 40% of their time looking for data or making sure they're using the right file.
I actually had a call recently to discuss this with the customer. And the guy was late to the meeting because he'd been trying to work out which NC file the operator should be running for an urgent part. During that time, his machines were idle, the operators were idle. Money and time were both going to waste.
This all boils down to how we tie our data together and how we manage change of that data. Most companies I visited aren't able to easily say, "This is the packet of data for that project. Here's the documentation, the machine tool specifications, the drawings, NC files, work instructions."
If there was an issue during production at any point in the past, can we easily look back and see what was changed in the process, why things work the way they do, who reviewed them, and who reviewed the process definition, and the things that changed? How many times have you needed to produce a repeat part and struggled to find the correct set of data?
This ultimately leads to part quality issues. If we don't have a way of pointing to the current standard, we have confusion and uncertainty about what we should do. This ultimately leads to either scrapped parts that are produced to the wrong standards, time spent doing rework on parts to get them to the correct standard, or time spent working with our customers to get an exception for being non-standard.
And at the heart of all of this pain are the superheroes we employ. These pains aren't caused by the people and their lack of ability at an individual level. They are all highly skilled and hugely capable.
But we aren't harnessing their skills to their full extent. Too much work is having to be done out of hours and with too many non-value added tasks. All this leads to reduced job satisfaction, lower effective output per worker, reduced individual work quality, and no opportunity for employees to innovate or improve processes.
I'll give you an example of a conversation I overheard at a customer recently. I was in the CAM office for this customer doing some work with one guy who was the interface between design and production. One morning, I sat there with my cup of tea. And this is how it played it out-- the shop floor guy comes in.
"Morning, Bob." It's not his real name, but I'm covering his identity. "Morning, Bob, what's on the list to do today?" "Well, it's on the board, isn't it," says Bob.
He points to a whiteboard full of loads of paper attached to it with magnets. "Which one first, Bob?" "Starts from the left, like always."
The operator takes the first set of sheets and looks through them. "Bob, what does 40 mean?" Bob explains. "And the 60, what does that mean?" Bob explains.
"Where are the files for this job?" Bob explains, "They're on the network, the same place as always." "Can you transfer them to the machine for me, Bob?" Bob sighs. Sure.
Bob then picks up the phone and calls the design office to speak to Alex. Alex isn't in yet. He'll call back later.
Bob explains to me that Alex has sent the CAD down, but hasn't split the geometry out in the same way that Jane does when she normally works on these pieces. She's on holiday this week and Bob doesn't know how to do it, so needs Alex to do it when he gets back in. Bob now needs to monitor his emails to see when Alex has sent it over before he can get on with his work.
What do we think about Bob? He's super capable, but doing multiple jobs and doing lots of tasks he doesn't need to do or aren't his responsibility. He's working hard, but he's frustrated.
He's wasting time, processes aren't well defined, unable to adjust to varying workforces. Downstream, people aren't clear on what they need to do and are wary of doing the wrong things. I could see them wasting time, money, and potentially quality, all at the detriment of a human element.
So let's talk about digital transformation and what it looks like. You might have seen this image before. If you haven't, then what we're showing are the stakeholders in the company and their points of interaction.
We can see lots of interaction, each red line taking time and energy. Many different products are in use. That's OK, but they aren't well connected. Each product is doing a particular job at a particular communication point. There are lots of different file formats, everything being sent here, there, and everywhere.
The designer Make Report talks about connecting teams, improving communication, and expanding collaboration. But the thing that I want to focus on today is from design to done, particularly "to done" part, as this is where the assembly and manufacturing happens. This diagram is representative of most of the manufacturers that I talked to. You might recognize some of the elements yourself.
It shows an over-the-wall mentality and data silos, with files being thrown over the wall either via email or network file shares. There's high levels of digital maturity upstream for the design guys. They have centralized data repositories for their designs, with workflows and approvals around that data.
But the far end is immature. There's a lot of paper-based processes here-- Word, Excel. They're common tools. USB memory sticks are used for file transfer. This brings IT security issues and loss of control of our IP.
As we move towards the right and digital maturity reduces, the amount of wasted time increases. And communication becomes less efficient. Or to put it another way, we end up with two teams. One side is digitally mature and the other is immature, with one side saying to the other, let me know when you've made it.
Let's take a look at the scale of the problem-- Bob's company. They have 21 designers, Bob in the middle. And there are 40 people doing things like production scheduling, workstation operation, maintenance, process engineering, QA. The list goes on.
The largest group of people, two-thirds of the company, are the ones who are digitally immature. And these are the ones who are making the final product. They are communicating badly and are poorly connected.
As I talked about earlier, change is difficult. It's not a 60-second makeover. One of the main reasons we are still digitally immature is the scale of the problem and the number of people involved.
We look around our facilities and see so many people interacting in different ways, using many different software and hardware tools. We worry about data, people, processes, our customers, their customers, our suppliers, legal constraints. The list goes on.
Suddenly, our destination is unclear. And we're so busy investing time today, we don't have the clear capacity to think about tomorrow. Transformation is a journey.
And as with any journey, we should be clear on where we're starting from and what we want our destination to be-- our goals. We then need to know how we'll get there, what stops we will take along the way. Every stop we make should have a purpose and get us closer to our destination.
So what are the steps on our digital transformation journey? How can we make an impact on a continual basis to keep transforming and adding value at every step? How does each step of the journey individually get us closer to our destination?
And what does the destination look like? Here we see the digital maturity designs on the left, but there is a lot of what we're missing out on. Remember who we're focusing on-- those 40 people who are digitally immature. That's the area we're looking at.
What areas are we focusing on during transformation for them? The first part is the Bill of Process. Here, we want to define the steps that we go through to manufacture things, the resources we need, the people and skills we need, the tooling, raw materials, and consumables, as well as the work instructions.
We want to version control this so we have great control over the definition of it, how it's reviewed, how it's approved, and how it's published. That, then, leads us onto manufacturing execution and scheduling. How do we define the schedule of production? And how do we track what happens on the shop floors?
How are we able to react to change when it happens and replan? Then, we have QA to worry about-- not just how we ensure we're going to make the right parts or the right standards, but how do we use QA and change orders to manage changes to that Bill of Process?
Too often, I've seen Word documents where there's a table at the bottom of the document that says, Bob changed this on the 1st of July. It doesn't say why he changed it, just says he did. There's no traceability back to the root cause.
How do we bring in the supply chain? How do we bring in those teams into the process so they have live access to the same data we do? How about the service and maintenance teams? So rather than maintenance being an afterthought, it becomes part of the process.
After we've done all of this, how do we start using metrics more? Now that we have all of this data, how do we get visibility of the costs and bottlenecks? And how do we start making targeted process improvements?
So back to this diagram. Of course, it's abstract and illustrative. If you were to map out your interactions, what would it look like? Let's take a look at an example customer.
In this example, we have CAD and CAM engineers using a network file share to store their files. We have our production manager taking the list of orders from the ERP system via CSV files or an Excel spreadsheet, and compiling it into a production schedule that gets stored on OneDrive. We have our process engineer and the QA engineer, also contributing to OneDrive.
Eventually, all of this gets printed out onto paper copies that are distributed around the shop floor and passed to the work cell operators in the workshop. The latest NC files and work instructions are shared via USB stick or our network file shares. Meanwhile, there's a vast amount of email communication for change requests or process clarification and updates. So how do we make this better?
So step by step-- firstly, we might deploy a centralized file storage system, a document management system such as Vault. So now our CAD engineers and CAM engineers can collaborate on a single data repository, with version control and life cycles around the data. Our suppliers can contribute and have access to the data through gated access portals. We can even connect our machine tools and our machine tool operators, allowing them to automatically push and pull files to the machine and view the latest published work instructions. Any changes are easily pushed back to Vault for review.
When it comes to production scheduling, we can create a live schedule in Prodsmart that drives production, rather than being an artifact at the side of it. We can see what is currently happening and react to change. We can also record our QA results against the jobs.
We can then start to remove the email conversations by using Fusion 360 Manage. We can capture that well-defined Bill of Process that's reviewed and approved. We can use Change Order Management. We have control over updates that are made to the process and trace them back to the root cause.
So what might a full platform solution look like for a customer? This is an example of a hybrid system where the CAD and CAM data is stored within the network and worked on using desktop products, with the processed data stored in the cloud. Inventor, PowerMill, and the machine tools are connected to the Vault with full traceability of the data. Work cell operators can see all the way up the chain, and be sure nothing has changed before they do their job.
Prodsmart is used to schedule work and track the live production process. The ERP system is integrated with order details passed into the production schedule, and live cost data fed back in return. Fusion Manage is used for the process engineering. Factory Design Suite and Tandem are used to plan the production layout and compare expected to actual, allowing for replanning and improvement of the factory.
Vendors have live but gated access into our data so they, too, can collaborate on the correct versions of data. Also, this fits well with integrated factory management. If we're digitally capturing our assets, then it's natural to also want to capture the process that is running on those assets.
Let's look at another potential platform solution. Everyone's solution might be different depending on their pains, business constraints, and the systems they deploy. This example is more cloud oriented. Here, we have a third-party PLM, CAD and PDM system.
Those designer guys are digitally mature in their third-party system, but we have so many pains further downstream. Remember the 40 people from earlier. We can get connectivity, either tightly integrated or loosely, with reference metadata between the third-party system and the Fusion platform.
In this example, we have used Fusion Team and Vault in combination for our manufacturing CAD/CAM and NC files. We have Prodsmart and Fusion Manage as before, for our process engineering and production. But this time, we've also made use of the Autodesk Platform services, or Forge, to aggregate data from various different products and tools to provide both an internal overview of the data, as well as granting third-party access into the live data.
Let's look at how we can improve things for two departments within the same company. In this company, they have their inventor guys who are already digitally mature. They use Vault and Fusion Manage for their part design.
Now, in production, we have two departments-- one department that works on part machining, another that produces fixtures and tooling. One team works in Feature Camp, the other in Fusion 360. There's currently poor levels of communication.
Everything is done via email and meetings. There's little to no traceability. And the current file storage method is network drives.
The solution here is to improve communication and collaboration between these teams at the data and process levels. By introducing version control and workflow around the data, it's clearly communicated what the latest file versions are and what stage that data is at. The process engineering allows the two teams to align around the product.
The Bill of Process for manufacturing the part will call out the tooling required. And the tooling department will integrate with the product teams at this point. Requirements for the tooling are clearly communicated, with traceability to the latest approved designs.
Feedback on those designs can happen in context. And most importantly, when we release the Bill of Process, we also release the tooling definition as a complete data set. Now, when we deploy this to the shop floor, the operators get clear instructions about which version of the workholding to use, as well as easy access to the correct data sheets for how to operate those items.
Any change requests are easily communicated back. And the modification process spans all departments. Having understood our pains and our objectives, we are now combining products and tightly integrating them with a clear purpose. We've created a platform on which we can improve communication, increase collaboration, and be clear on traceability between data points.
So let's look at some of the puzzle pieces that can be deployed during digital transformation. First, let's look at data management. Here, we're looking at the manufacturing extension for Vault, or Vault for Make, as it's also known. This was a utility developed in my team.
Let's look back to this over-the-wall mentality-- people working in data silos. On the left, we have the digitally mature designers, like I've said before, with good workflows and collaboration around the data. But then, they throw that data over the wall to the CAM guys.
They do the programming. They save their projects to a network drive, with a naming convention of we have A, we have B, we have Bob on a Friday afternoon. They then throw the NC files over the wall to the guys on the shop floor, who keep the NC file copies on the machines and are never sure exactly which file is the latest one.
We've got two main issues. The lack of revision control around the data-- how do we know which is the released version of that data? A lack of traceability-- if an update is made in the CAD office, how do we know that we received it? And how do we know which version of the CAD is currently in use?
So what's the solution? Here we have the CAD guys already involved. They now release their designs to the CAM office, who can use a plug-in within Feature CAM and PowerMill to import the CAD and create the traceability links. They can store the CAM projects and supporting files within Vault, and move them through life cycles before passing them to the shop floor.
Here, we have a utility that connects Vault to the machine tools. This allows operators to always use Vault as a source of truth and deploy the files directly from Vault to the machines. Now you can see the full traceability chain.
So before they hit Cycle Start, they can see whether anything has changed upstream, and be sure they're working on the latest specification of data. If NC code is changed on the shop floor, the new revision can be checked into Vault and fed back upstream, in order to improve future CAM programming.
So the benefits here are we now have traceability to CAD. We know what revision we're working on. We know any updates are automatically notified to users. We no longer need to worry about missing email updates.
Revision control over all our CAM data means we now can be certain about what is the correct version of files. We have removed the need for unnecessary communication to clarify which is the correct version of a project. Life cycles around the CAM project can show us what data is in review and what is released to production.
If updates are made upstream, we get notifications allowing us to stop production and prevent scrap being machined. For the machine tool integration, operators no longer need to store files on the machine tools. Vault becomes that source of truth.
We can apply life cycles to the NC files, so it becomes clear when files are proven and can be run on unattended, or unproven and need to be run with care by a senior operator. Standard interfaces to multiple different machine tools mean that operators can work across different machines and have confidence in what they're doing.
Let's look at production scheduling and tracking. What does this look like for manufacturers today? Paper travelers are still used by many people-- packets of data that move around the factory with the parts.
Whiteboards are used for scheduling. This schedule does not directly drive the production, necessarily. It just indicates what to do next or may even just be very high level. You have to then go and find the data that supports that process.
As shown earlier, everything gets printed out and distributed to the shop floor. If there's a process change, we have to work out who has the old forms and get them swapped out during production. At the end of the process, we'll enter the data from the forms into an Excel spreadsheet. This will include any QA data.
I went to see one customer. They were taking measurements on the part, writing them down, entering it into an email. Someone else was then copying it from an email to Excel for reporting. It seems inefficient, but they felt it was OK. They knew that mistakes were made, but they just dealt with them.
This is fairly typical. How many times have you seen a paper travel that cannot be read or has been lost? We only capture the data at the end of the process, with no visibility about the live status of the factory.
Reaction to change is hard. High levels of communication are needed to find what parts are where in the factory. Delayed data capture means delayed visibility, which in turn means delayed problem solving. And the data is difficult to analyze, so there is no long-term analytics to help improve production processes.
The result of this poor communication, lack of visibility, inability to react easily to change, leads to a lot of waste, whether that's scrap or time. It could lead to quality issues or missed deadlines. Costs rise and end customers become unhappy.
Let's focus on three benefits of digital transformation here. We can now plan ahead and schedule resources. We can react easier to change, as we have a single schedule for all our resources.
Data is traceable, with the correct information shown to operators in context. No more hunting for data or asking Bob what to work on next, and what things mean, and where the NC files are. We have confidence in the decisions made and actions taken. We have real-time visibility of what's going on, meaning we have real-time decision making. Those decisions are better, too, as we're using the latest information in context.
We can also then connect to other tools in our ecosystem. We can push order details from our ERP system to our execution system. Job numbers, quantities, any customizations required, and expected due dates are easily passed between systems. No need for manual entry and mistakes.
During production, we can push information back. This might include predicted completion dates, as well as updates on costs. Those include our human costs, our consumable costs, as well as our scrap and rework rates. This gives us live cost management and reporting. We can keep our customers up to date on when products will be delivered, and keep a close eye on our business operations.
What about process engineering? We can define the process in Fusion 360 Manage. Here, we can document the resources and skills required. We can link to files involved or other document management systems.
Everything is version controlled and can be reviewed, approved, and tracked. This is the change management I talked about earlier. We're now applying change management not only to design data, but to the process of production.
We can see who changed what, when, why. And it's all traceable back to the QA systems. We now have a starting point for our data packages, a single place where we can go to point to say, this is our project data.
And what does Fusion 360 Manage look like? We already captured our manufacturing bill of materials in Fusion 360 Manage. Now, we can drill down into our Bill of Process for each item to be produced.
We can see the steps in the process, with each step being revision controlled. We can drill into each step and see the resources needed, the work instructions, and any other associated MBOM items such as fixtures or work holdings. We can also connect Fusion 360 Manage to Prodsmart. That process that was reviewed and approved in Fusion 360 Manage can be pushed to Prodsmart for execution and scheduling.
And how does that QA work? We might create change orders for multiple reasons-- non-conformities during production, process delays that highlight errors in the workflow. Repeated unscheduled maintenance might highlight issues in the process that need changing or optimizing, or just general day to day improvements.
They would all go through the process of making updates, reviewing the changes, and then releasing them to production. All of this allows us to see what changes in the process when, and tracing this back to the root cause. This saves time when trying to understand the decisions that were made during the design of the process. It reduces uncertainty and the need for unnecessary communication.
Let's look at a couple of success stories. This is a story about National Oilwell Varco, NOV for short, and their fiberglass systems team based in Plymouth in the UK. They produce composite parts using one of the largest CNC machine tools in Europe, at 30 meters by 6 meters by 2 meters.
Here, we deployed one of the first instances of the manufacturing extension for Vault. We integrated PowerMill and Vault into their production process. The three main successes are seen on the right.
Firstly, we reduced their lead times from three to five days to 20 minutes by improving collaboration. Let me explain. Previously, their design teams created the designs, and then reviewed them. These reviews would take a few days, and would often result in minimal changes. Only after the review was complete would the designs be passed to production, who would then need to program them before passing them to the shop floor.
We added a new workflow around the CAD to include two release dates-- release to programming and release to production. When the designs are sent to review, they're also sent to programming. The state of the files clearly indicates that although the designs can be programmed, they aren't ready for manufacture yet. So the programmers get a head start.
Once the designs are approved and released to production, the programmers just need to update the CAD and recalculate any impacted tool paths before outputting the NC. Remember earlier, when I mentioned two customers who talked to me about spending 40% looking for the right data? This company reported a 30% reduction in time to find data. This is all thanks to having a single data repository that's version controlled with life cycles around the data.
The customer also now has an unproven/proven workflow around their NC files. Operators can be sure when they can and cannot leave the machine unattended to do other work. This removes the need to ask questions and reduces unnecessary communication.
The next story is about the Birmingham Technology Center, the office where I'm based. This workshop serves two purposes. Firstly, we host a variety of hardware to prove out Fusion 360 and our other make products. Secondly, we produce real parts for customers, including aerospace components.
We want to hold ourselves to the highest standards and have achieved ISO19001 and AS9100 certification for quality management systems. The team at the Technology Center have implemented a solution that pulls together Fusion 360 Manage, Fusion 360, PowerMill, Fusion Team, Vault, and Prodsmart.
The value they've achieved at zero rejections and time saved. The jobs that need to be done are cleared to the operator. And work instructions are fully defined, with links to critical data items.
Traceability runs all the way through the data from CAD through to the inspection process. Quality improvements have resulted in no deviations across parts, regardless of who the operator is or which shift. Because the instructions are clear and precise, we can ensure consistency.
Zero scrap is hugely important in aerospace, where parts can be worth hundreds of thousands of dollars. Finally, all rework is traceable, from the nonconformity through to the corrective actions required to correct the issue and ensure that no future issues arise as a result of the same root cause. In the future, they plan to improve their cost aggregation. This might include the reporting of equipment [INAUDIBLE], time tracking of operators, and consumable costs.
So what else does the digital transformation empower us to do? What other values might we be able to realize with the help of digital transformation? Data aggregation is the act of bringing together a cohesive set of data from multiple sources, reporting on that data to give insights across the business.
As I said earlier, it's OK to have multiple products involved, but the key is to bring them together effectively to deliver value. We can use our software APIs to aggregate the data, and dashboards and reports to view it. Automation is now easier. When a new version of a design standard is released, we can notify anyone who has consumed it further downstream.
When a new version of a die is created, we might automate the moldflow advisor process and automatically store the results. We can then notify the approver with a hyperlink to go straight to a web page where they can view the result and simply provide a go/no go acceptance. We can now work cross site and cross geo. Having workflow states and single repositories make it easier to find data and makes it clearer about whether that data is ready to be consumed or not.
We can easily redeploy work to other sites or countries. We can also easily do repeat orders. We no longer need to hunt for that data package.
This all helps towards our sustainability goals. We're reducing our waste, our energy usage, and our consumables. We can also innovate easier. If we are clearer about what we're doing today, we can improve more easily for tomorrow.
So in summary, where do you and your company fit in all this? Thinking about change, where are you in that process? Are you ready to change but not sure where to begin? Are you trying to change, but have had issues in the past trying to wrangle all your existing data and processes?
Does your company have that over-the-wall mentality I've mentioned-- of course not intentionally, but is that something you recognize? Are your products disconnected? Are they doing a great job individually, but not achieving what you need as a whole? Are you already using Autodesk data management tools in some areas of the business, but not others?
Your first next step, your low-hanging fruit, might be to simply get more departments collaborating on the same data platform. Do you have the digitally mature design teams that need to be connected to the immature production teams? What collaboration opportunities might you unlock if you can connect them? What delays and costs can you reduce if they were better connected?
So my summary is this-- start your journey. Identify your pains and solve them one by one. Every step on the journey should solve a pain and bring its own benefits.
Focus on data improvements. We've seen how they can bring you shorter time to market and break down silos, like with NOV's fiberglass systems team. Focus digital maturity around the human element and what you're trying to solve. Look at the tools that are available to solve those problems, how they will interoperate and allow you to be more efficient.
Each step along the way will increase your confidence and resilience, too. The workforce will see the benefits and buy into it. They'll expect things to be more streamlined, be keen to innovate and improve processes, now they're free from the mundane and the headaches of communication.
Finally, what can you do to start this journey? Firstly, people involved-- think of the red arrows diagram. What does it look like for you? Do stakeholder mapping. Who are the people involved and what are their roles? What are their current points of interaction? What information is shared during those interactions?
Secondly, focus on the motivators for change, the pains, and the costs. What works well and what doesn't today? What are the pains in the process? Where are the costs incurred? How often are they incurred? What is the cost to the business unit? What is that return on investment?
Thirdly, look at the capability and the solutions to the pains. Here's where we spend a large amount of time with our customers. We can spend up to 50% of our time on some projects, making sure we understand the customer's way of working and their human objectives. Investing time here ensures that the final solution is a success.
So what technology can be used to solve the pain? Is that configurable, off-the-shelf software? Or do we need to create something custom? Be clear about what the expected goals and the values are and make sure you have well-defined requirements.
Then finally, create a step-by-step action plan. Make sure you deliver value as you deploy each one. Rank those solutions by importance and difficulty.
Your low-hanging fruit are those items that are important and easy to implement. The luxury items are the less important ones that are difficult to implement. Once you have these defined and prioritized, you can start your digital transformation journey. Thank you and good luck.