Digital Transformation for Process Improvement in Manufacturing

KEITH ROESER: Welcome to AU 2024. My name is Keith Roeser, and I've been with Autodesk for over three years as a senior professional service consultant. I am part of a consulting team that works mainly with enterprise business accounts. The subset of EBA customers I specialize in are the ones in the manufacturing space, mainly large machine shops.

These customers generally have manufacturing locations across the globe. All of them struggle with the same things as small mom and pop shops struggle with, and that's managing their data. One difference between the two is these large EBA customers have more projects, staff, equipment, and assemblies to manage. The other main difference is these EBA customers have machines and product lines strewed across the world, but if you think about it, that isn't dissimilar to the small shops with suppliers that can assist when they're overloaded.

My hope is that, whether you're a large company or a small startup, you can gain knowledge that will help you manage the data you already have more efficiently. Here's an overview of what we will be discussing today. First, we will look through-- we will go through a brief history of the digital transformation journey and some of the terms often used.

Next, we will have a look at-- we will look at the ways to identify where you and your employer are located along the journey. This journey does have milestones and checkpoints, but you'll never truly arrive and be done. Thirdly, we'll discuss how to apply the correct metrics to give your organization the best chance for being successful. We then will review what the statistical data tells us about our data. Lastly, we'll review some of the solutions we have here at Autodesk.

Now, let's get started with a brief history of digital transformation. Have you spent any time at all researching this subject? You have probably noticed that there is a lot of opinions and information out there, but how is it all intertwined?

Does the term digital transformation feel like a word search without any clue of what you're looking for? I hope our time together demystifies a few of these terms for you. Knowing these tools and how they differ will help you get started off on the right foot, quicker.

Creating this deck brought to mind a very old skit by Abbott and Costello. I'm not going to play the whole clip, but wanted to share this as I think a lot of us can relate. Sometimes, you can be speaking the same language, but have no clear understanding or answer to the question you had than before you asked. This especially holds true when discussing data.

[VIDEO PLAYBACK]

- Well, let's see now. We have, on our team, we have Who's on first. What's on second. I Don't Know's on third.

- That's what I want to find out, the guy's name.

- And-- huh?

- That's what I want to find out, the guy's name.

- I'm telling you. Who's on first, What's on second, I Don't Know's on third.

- Abbott, you got to be the manager of the baseball team?

- Yes.

- You know the guys' names?

- Why, Sure.

- Why don't you tell me the guys' names on the baseball team?

- I tell you, Who's on first, What's on second, and I Don't Know's on third.

- You ain't said nothing to me yet. Go ahead and tell me. All right, you got a first baseman.

- Yeah.

- When you pay off the first baseman every month, who gets the money?

- Every dollar.

- [INAUDIBLE]. Who does it?

- He does. His wife comes down and collects it.

- Whose wife?

- Yes. [INAUDIBLE]. He's earned it.

- Who did?

- Yeah.

- [INAUDIBLE] to myself.

- So they tell me.

- Yeah, I get behind the plate. I'm going to do some fancy catching, and Tomorrow's pitching on my team. Right?

- Yeah.

- Now, Tomorrow, he lines up the ball, and I'm behind the plate, and a heavy hitter gets up. That heavy hitter gets up, and he's ready to hit the ball. And Tomorrow's going to throw the ball. I'm going to catch it. Now, I'm going [INAUDIBLE]. Tomorrow throws the ball, and the guy bunts the ball. Now, when he bunts the ball, me being a good catcher, I'm going to throw the guy out at first base. So I pick up the ball, and throw it to who?

- Now, that's the first thing you've said right.

- I don't even know--

[END PLAYBACK]

KEITH ROESER: Since we have a short time today, I want to focus our time together on four main tools under the digital transformation umbrella. Digital transformation is a very common phrase that can mean many different things depending on what your focus is. It is similar to the current buzzword artificial intelligence.

Digital transformation resides under the umbrella of AI. The acronym SCADA, MES, ERP, KPI, and SPC, and many others, are a subset of what we refer to as digital transformation. The first acronym that I want to discuss is Supervisory Control and Data Acquisition. This term was coined in the 70s and encompasses the idea of creating a tool that does not require specialized training to automate the control or ability to acquire data.

Prior to this time, the acquisition of control was only available to large corporations, and these corporations, they required someone on prem to identify the need for change and pull a lever or rotate a dial and record the change. Later, there was a shift to relays, but these solutions are very binary. This hardware also doesn't allow for reconfiguration or flexibility.

Timers have a similar limitation. If you take a sample every hour, but the line stops for maintenance for 15 minutes. It will not give you a great data point without someone noting the fact that one of the operations was down for a quarter of that time. With the advent of local area network and Structured Query Language in the 1990s, we now have modern SQL web based applications that allow for real time data available globally.

This has solved two main issues. One, you are no longer limited to on premises personnel. Secondly, you do not need to have specialized staff to set up these solutions.

Manufacturing Execution System, or MES for short, was officially termed in 1992. MES gives us the ability to see the status of production processes in real time, avoiding possible incidents like unexpected stoppages. It organizes data to help improve product quality by detecting possible faults, guaranteeing product traceability, plan manufacturing, and eliminate paper and fostering continuous improvement of the processes.

It is the most efficient way for a factory to repeatedly know everything that happens during the manufacturing process of a product. Some other benefits that are worth noting are the ability to rapidly respond to changes and document easily when the change occurred, allow for root cause analysis, enable fact based strategic decisions.

The diagram on the right shows the process flow for MES. Clearly defined objectives in the top layer, labeled here as strategic initiatives, cascade down to the bottom three layers. Like the cascading down of strategic initiatives, the results emanate up from each of the bottom three layers to the strategic initiatives level.

Originally known as MRP and developed by the Case Corporation in the 1960s, Enterprise Resource Planning is a comprehensive system that consolidates all aspects of business, including customer relationship management, material require planning, supply chain management, and more. Some of the big names in the ERP space include names like SAP and Oracle.

There were a few other big names in this space, but most have been bought up by these two. ERP can track many key data points including the root cause analysis of abnormal stock levels, recommended maintenance intervals required by monitoring the out-of-tolerance components, report [INAUDIBLE], predict future needs, and give you a real time look at operations on the production floor.

Oftentimes, the role of MES and ERP are confusing to new folks along the digital transformation journey. Here's a chart of the key differences between MES and ERP. MES focuses on the process of manufactured goods, while ERP has a much broader focus.

MES collects data triggered by an event in the manufacturing process, for example, an operation one was completed on machine D, while ERP would be triggered by an operational event such as a customer order. The shop floor personnel would mainly be interacting with the MES system, while other systems would be incorporated in interacting with the ERP system. Data captured in the MES system is consumed instantly or relatively quickly, while data captured in the ERP system is analyzed in a more long term and strategic manner.

Key Performance Indicators are measurable values that the business can track and assess its effectiveness of their strategic initiatives. There are five main KPIs, financial, customer, operational, employee, and marketing. The origin of KPI is unknown, but the roots have been traced back to the Wei dynasty in China approximately 201 to 300 AD. The first recorded use of a KPI dashboard was discovered in a Scottish cotton mill in the 1800s. The stations had wooden blocks above them that were color coded for traceability.

Similar to KPIs, Statistical Process Control is a way of checking the health of an organization. Analysis of key metrics associated with the production of a component with the goal of assuring that the process, as it is operating, is consistent with the customer requirements. It also ensures that the process isn't drifting from an unexpected and unexplainable manner, which would lead to a large amount of defective products.

SPC is designed to transition manufacturing away from a traditional inspection driven model towards one that is a prevention based, which is less expensive and more efficient. This prevention based model works to fix issues with machines and processes before the products are even created, thus reducing scrap, saving valuable time, and controlling costs.

Now that we've had a look at these systems, or how these systems came into existence, and the kind of data they're used to collect and analyze, let's look at the stages of digital transformation. Once you can identify where your organization is along the journey, you can better understand the next logical step to take.

Stage one is often referred to as the ad hoc stage. Organizations at this level are just beginning their digital transformation journey. Here are some key characteristics. Number one, processes are not well defined. Efforts are often reactive rather than proactive. Number two, technology is basic, and there is little to no interaction between systems. And finally, successes are often due to individual efforts rather than structured approach resulting in predictable outcomes.

Stage 2 is often referred to as an early adopter stage. Organizations at this level have begun to develop a more structured and consistent approach, although they are still not fully optimized or integrated. Here are some key characteristics. Basic processes are defined and documented, but still very inconsistent. Digital efforts are confined to individual departments with limited collaboration, and finally, digital strategy is fully aligned-- isn't fully aligned with the overall business strategy.

Stage 3 is often referred to as the consistency stage. At this level, organizations have established a well-defined and standardized process, and there are greater alignment with overall business goals. Some of the characteristics are, there's greater collaboration across departments and functions. The strategy is well defined and aligned with the overall business strategy with a clear vision. Projects are consistently successful, delivering tangible benefits and value to the organization.

Stage 4 is often referred to as the sustainable stage. At this level, organizations have advanced optimized processes and are leveraging digital technology to drive continuous improvement and innovation. Listed here are some key characteristics. At this stage, the focus should be on maintaining this level of excellence, exploring new technology, and continually evolving to stay ahead of the competition.

Stage 5 is referred to as industry leaders. At this highest maturity level, organizations have leveraged data to drive continuous innovation, maximize efficiency, and create new business models. Characteristics of this stage are listed here. Systems and platforms are fully integrated, enabling real time data analytics and insight driven decision making at all levels. The organization often acts as a leader or orchestrator within its ecosystem, driving industry standards and collaborating with other entities to create value.

Now that we've had a look at the stages of the journey, I'd like to discuss something we all forget to do sometimes. We often understand the need to make changes and roughly the steps, but we forget to define what success looks like for other views outside our own. In the following slides, we'll look at a few personas that are very common in the manufacturing space. Obviously, every situation is different, so it's important to have a thorough review of who needs to be involved.

Just like this topic, the list of stakeholders will evolve over time. It's important to build this list with a group and not through a lens of an individual contributor. Each have their own needs and definition of success. Some personas may seem obvious, while others may seem to be irrelevant at first.

As an engineering director, my key challenges include dealing with unpredictable and costly changes, ad hoc shop floor design planning, and insufficient collaboration with the supply chain, all of which drive up costs. My main objectives are to improve planning efficiencies and foster better collaboration across the team.

As an engineering manager, I hope this journey will improve design quality while simultaneously reducing costs. My plan-- my pain points include continually evolving regulations, ensuring employee safety, and reducing downtime and maintaining equipment assets. Successful outcomes for me include minimizing the impact of planned closures, decreasing unplanned closures, and reducing defects at handover.

As an industrial engineer, my pain points include maintaining equipment, reducing downtime, collaborating with a diverse team, and identifying risks early. My desired outcomes are to improve data exchange, meet regulatory requirements, increase asset resiliency, and reduce safety incidents.

As a facility engineer, my definition of success involves efficient process analysis, risk free layout designs, and integrated supply chain management. My pain points are maintaining equipment, reducing downtime, and identifying risks early. I aim to improve data exchange and reduce safety incidents.

My definition of success includes having a holistic overview of project tracking, reducing contingency budgets, and achieving zero safety incidents. My pain points include accurately estimating workload, managing inevitable changes, and identifying completed tasks. On the digital journey, I aim to improve forecast accuracy, schedule control, and cost predictability.

Now, you've probably noticed that several interviewees mention the same things, but they also have vastly different responses. This is why you need to give everyone a voice. It also helps when implementing change if everyone feels as if they had a say.

So what does the statistics tell us about data in manufacturing? The convergence of people, processes, and technology hinge on data. When these four elements unite, optimized operations and accelerated growth become achievable. Harnessing the full potential of your data is one of the biggest challenges and opportunities you face today.

To draw a simple analogy, think of data as the wood scraps from the early days of Henry Ford's assembly line. It's something you're generating anyway. These wood scraps became the foundation of a profitable business called Kingsford charcoal. While data is far more complex than wood scraps, its potential uses are vastly greater.

According to the International Data Corporation, over 90% of data generated, including enterprise data, is unstructured. This creates a significant data problem, limiting the usability of data for business. The data being generated is complex and often disconnected and trapped in proprietary formats within overlapping systems and departmental silos.

Furthermore, 68% of data available to enterprises is not utilized, creating a big data problem that limits the usefulness of data for businesses. Nearly every manufacturer we speak with face broken processes and disconnected systems where data is manually re-entered instead of being reused. This data often exists in multiple formats, combining both digital and analog information.

At Autodesk, our mission is to maximize the value of your data. Whether it's in production output or machine utilization or energy consumption data, we help customers transition from a traditional product lifecycle to connected digital processes. Our goal is to make your data granular, interoperable, and accessible, ensuring it is in the right format to work for you.

Imagine what you could achieve if 100% of your data is usable. Usable data can help you understand the health and performance of your business, identify where to invest resources, gain efficiency, reduce costs, and streamline operations. Digitalization followed by connected data are foundational steps leading to automation and insights.

Connecting data enables you to automate processes and generate value insights today, allowing you to solve problems before they occur and predict outcomes. This adaptability ensures resilience against future challenges.

Now, let's have a look at the tools you have access to within your Autodesk account. Here at Autodesk, we're focusing on building a platform that is truly the next generation of technology, a new way of working fueled by unique capabilities and connected data. The Autodesk platform consists of three industry clouds, Autodesk Fusion, Forma, and Flow, and a set of underlying cross-industry APIs and services referred to as the Autodesk Platform Services.

The platform is connected by comprehensive and resilient data architecture we call the Autodesk data model. In the middle layer, you see pictured. Autodesk data model will manage, organize, connect, and connect project data across your industry clouds, but even more importantly, across all of our Autodesk products and third party solution, which will connect back to your enterprise resource planning solution of choice.

Within the Autodesk model, we are building a data model dedicated to manufacturing that will become a connected source across the entire organization, including supply chains, allowing data to be moved between desktop products and cloud capabilities, as well as third party ERP solutions like SAP and Oracle. Just imagine comprehensive workflows from concept to production across PDM, PLM, and MES, connected data across business solutions.

I would like to highlight three solutions that you have access to within your Autodesk account. The first one is machine tool extension for Vault, which will allow you to send and receive revision controlled NC code and PDF setup sheets to the shop floor.

The second solution is Fusion Operations, which was formerly known as Prodsmart. This solution has been fully integrated into the Fusion ecosystem and will allow you to start tracking OEE, storing revision control work construction, as well as tracking production on the shop floor. Lastly, you have access to Fusion Manage. This is formerly known as Fusion 360 Manage with Upchain.

The machine tool extension for Vault application allows machine tool operators to synchronize the files on their machine with the files in Vault. The operator can easily search for the correct NC file and send it to the machine. Any files modified on the machine can easily be sent back to Vault.

In this scenario, the files sent back to Vault will default to an unproven state before allowing the CAM programmer to accept or decline the changes. The application, along with the plugin, will allow for a seamless connection and knowledge of any CAD file changes taking place in the design office.

Fusion Operations is an MES system that is tailored to be a quick start solution that can be fully operational in three days. Fusion Operations is supported by a full API that can link to your current ERP system. Some of the other mid-term benefits include visibility in real time, accurate order management and access from anywhere on any device.

Long term benefits include data driven efficiency improvements by providing insights captured from your real world data. This data can start to be used to level load the production floor. Lastly, this cache of data can be harnessed to help the business make fact based investments in personnel, equipment, additions, and reorganization of the production floor if fed into tools such as Flex.

Fusion Manage is an extension that is available to you within the Fusion platform. It can be activated very easily from your Autodesk account. Fusion Manage will allow us to capture, notify, and view a full history of design changes to help manage compliance.

Key stakeholders can add comments and approve design changes in almost real time. Having all this stored in the cloud makes it the centralized location that can be accessed from anywhere by anyone in your organization on any device. Administrative tools allow access to only stakeholders that are relevant to this design.

Software alone isn't going to do anything. Data may be an underutilized asset, but people are your biggest asset. Before going and downloading every piece of software available to you and your organization, we need to have defined agreed upon goals. These goals, most importantly, must be backed by the business. Do you have buy-in from your manager? How about your manager's manager? Conducting BAWs is a vital step in the digital transformation journey.

My colleagues and I in the consulting team would like to work with you to conduct these workshops if given the chance. If consulting isn't accessible to you, here is a rough description of what a workshop consists of. I would recommend conducting a workshop at the onset of your journey.

Imagine, for a moment, what the future might look like. An order from a customer comes in for 10,000 valves. The project kicks off in Fusion Manage with an automated workflow to assign tasks and track milestones. The engineering team uses an existing 3D model from Inventor to begin modeling, and Fusion engineers automate the creation of hundreds of variations using generative design. The design are analyzed for optimal performance, ensuring they meet the customer requirements.

The customer adds a last minute note indicating a new weight requirement. Feedback is captured and instantly flows to the engineering team, which adds it to the generative design to create a new optimized version. The model is shared with sales, engineering, and the customer, and the new model is approved.

The production team uses Fusion Operations to plan, optimize, and resource the production run, ensuring an on-time production delivery. In this future, stakeholders are seamlessly connected, helping optimize resource allocation, reduce lead times and errors, and ultimately getting your product to market faster.

Today, regardless of the software you're using, you can take advantage of the connected data in the manufacturing data model. If you are using Inventor, you can push data to Fusion for manufacturing as well as generative and electrical design. If you're using Vault, you can connect to Fusion and collaborate and share data with other stakeholders beyond your organization.

We want to partner with you and help you get ahead of tomorrow's changes today. We have a rich history of digitally transforming ourselves as a company, from pen and paper to CAD Cam, from desktop to cloud, and now from point solutions to connected workflows. Our culture of ongoing innovation is combined with 40 years of experience helping customers digitally transform themselves across design, manufacturing, construction, architecture, engineering, and media and entertainment industries.

We can meet you at your data maturity stage today and accelerate your journey forward with our platform. Thank you for your time today. I hope you found our discussion valuable. I'd like to challenge you to take action on three items.

Conduct your own interviews to identify challenges that a solid digital transformation plan could address. Expand your interviews to include colleagues outside your usual circle to gain a diverse perspective. Put yourself in their shoes and take detailed notes from their viewpoint.

Using the data collected in action 1, define what success looks like from your team's perspective. Use these insights to assess your maturity level with your team and share your findings with your management team. Research and document the digital tools currently in use within your organization, focusing on their purpose and application. Schedule a conversation with your Autodesk contact to discuss your findings. Armed with this insight, they can help guide you on your digital transformation journey.