manufacturing - msc software

Manufacturing

Digital transformation made simpleKeith Perrin, Senior Director with Hexagon’s Manufacturing Intelligence division, looks at the obstacles to digital transformation and how Hexagon’s SFx platform is helping design, engineering and manufacturing teams take a pragmatic, focused and integrated approach to smarter manufacturing.

6 | Engineering Reality Magazine

It’s been nearly a decade since the vision for Industry 4.0, the digitisation of manufacturing, was announced, representing a foundational change in how an organisation delivers value to its customers.

However, ten years on, according to Accenture, only 13 percent of businesses have realised the full

impact of their digital investments, enabling them to achieve cost savings and create growth. What’s more the average digital maturity of manufacturers’ end-to-end operations overall is just 39 percent.

Progress toward the vision of Industry 4.0 clearly remains slow. To quote Accenture, for most

companies, “the vision of the 4th industrial revolution is still far from being realised”.

So, what’s going on?

At Hexagon we believe there needs to be a new approach to using traditional design, engineering, and manufacturing tools and technologies.

Volume XIII - Summer 2021 | mscsoftware.com | 7

Image from Accenture Report (2020) “The race for digital operations transformation”


Today, manufacturers want faster, more agile development schedules and manufacturing processes that are increasingly responsive to customers’ needs. To cope, we’re seeing a move to deploying the continuous improvement and deployment models that first took off in the software development world. However, some of the traditional design, engineering and manufacturing technologies simply have not kept up and struggle to offer the necessary level of speed and flexibility.

As a result, we think something different is required. However, before jumping to conclusions, we should take a deeper look.

What’s so hard about digitisation, integration and automation?

Constellation Research recently reported that 77.3% of CIO’S see digital transformation as their #1 budget priority for 2021.

When asked how they expect to achieve their goals over 50% of these same CIOs

were looking for near-term demonstrable success. When asked what they thought would dramatically improve ROI, right now, the most popular answer was telling: “Automation of the next most easily automated function and/or line worker tasks.” What’s more, when asked “How much ROI do you want to see?”, the largest group of respondents was looking for a 10% effective productivity boost on average in 6 months.

At face value this seems like a readily achievable goal. After all, digitising processes isn’t exactly new. From the 1950s on, with a distinct bounce in the 1990s due to the advent of the Web, digitisation has fundamentally changed the way we work, shop, bank, travel, educate, govern, manage our health, and enjoy life.

Rooting changes to design, engineering and manufacturing in ROI and value

We regularly hear that Industry 4.0 will increase efficiency, flexibility,

productivity, and sustainability and drive greater automation and cost savings.

Awesome, but where do you start?

Anyone with a background in design, engineering and manufacturing technologies knows how complex manufacturing can be.

Amid complexity, a lack of focus and priority is a real stumbling block to employing cutting edge design and manufacturing methods.

Simplicity and consistency are typically our friends here. Simple lists of improvement areas, coupled with equally simple comparative investment levels, returns and some indication of difficulty are often enough to get moving. Obviously larger, more capital-intensive projects require more due diligence than a small project, due to the larger risk involved. Therefore, it’s key to avoid this trap.


Don’t “boil the ocean”- focus, focus and focus

The issue is that digital transformation is potentially massive in its breadth. We can transform “everything”. At the end of the day, however, we must keep our business moving.

Minimising scope is a simple way to drive transformation. Achievable and realistic are watch words. Not only is there less to go wrong in a small-scale project, it is easier to track and measure success against key criteria.

This is a key idea around which agile project management is formed. Interestingly some of this is far from new. Toyota, Honda, Canon, Fuji, for example, are a few well-known companies that have been practicing “agile” for decades and have been instrumental in its adoption. What is new is the scale to which these ideas have been adopted, and the scale of agility given to us from modern IT.

The idea of incremental transformation is key to much of the success we see with cloud native software companies, powered by open standard, easy to use and fast-evolving computing technologies.

The focus on nearer term, more achievable goals can profoundly alter the way we manage product development. It redefines essential roles and responsibilities requiring focused, cross-functional project teams, and an emphasis on collaboration.

So, how should we be measuring success? According to the Product Development and Management Association, “Cost, time, and quality are the main variables impacting customer success. Aiming at these three variables, innovative companies develop continuous practices and strategies to better satisfy customer requirements and to increase their own market share by a regular development of new products.”

Similar, repeatable processes are a logical starting point, especially as they can bolster other elements, such as repeatability, metric gathering, control and compliance.

Armed with a simple outline of priority and scope of our potential projects, it’s possible to have an informed discussion about how we execute our projects, including who’s going to do this.

Don’t break what you already have

Unless you’re a startup, you probably want to avoid disrupting the very thing that made you great to begin with. Transforming an entire group or division can be fraught with challenges and represents a substantial risk to the business. To use an old IT analogy, somehow, we need to continue to fly our plane, while changing out the wings.

A key idea in the IT world is “bimodal”, which is the practice of managing two separate, but coherent, modes of work. Mode One is focused on predictability, and the exploitation of methods and processes that are known to add value.

Mode 2 is focused on exploration, and experimentation to solve newly identified challenges or areas of improvement.

With the idea of “bimodal” it’s possible to see how “the new” can be separated from “the old” without incurring a critical failure that can expose the current business. A bimodal approach allows us the luxury of figuring out how new methodologies and technologies can add value alongside older methods


of working, before introducing them to the mainstream business.

By doing this as a matter of course, it becomes possible to introduce at a manageable pace new ideas and methods that are both practical and transformative. As for who should be doing it, in most organisations it is simply those folks with a desire for change and some relevant expertise.

Unveiling the mystery of complex, ever changing, technologies …

Let’s start with some technology basics: IOT, connected hardware, connected software, digital design twins, digital process twins. digital facilities twin, AI, AI assisted design, ML, model-based engineering, model based manufacturing, composite architectures, algorithmic trust, formative artificial intelligence (AI), blockchain… Wait, stop!

If you think that’s too much jargon, it isn’t the half of it. Gartner alone tracks and categorises some 1700 unique technologies.

Understanding these technologies can seem tough. Understanding where these technologies can add value is even tougher. If that wasn’t bad enough, these technologies change, a lot, often.

That said, many technologies represent relatively simple and not very new ideas: Ask anyone who’s been around CAD for any length of time what they think about digital twins.

And although many vendors like to present their tech as if it were a religious act, with associated technology rituals, jargon, and rites of passage, understanding the tech is not usually the challenge. The challenge is backing the right technology to implement a particular idea.

The questions then become: How mature are these technologies? Can they scale? What’s their longevity? Are they on the bleeding edge of obscurity? How much customisation do they need? How to avoid lock-in? Will they deliver ongoing value?

Often as not, however, the folks trying to make sense of this technology are

the ones who need to use it. Their day-job, sadly for all the technology vendors out there, is not to evaluate our technology. It’s to improve products or the processes they’re responsible for. They simply need practical tools.

In the application development world, people overcome complexity by using a configurable set of reasonably interchangeable services.

If you’ve ever looked at PaaS (Platform as a Service) service catalogues, you will have an idea of what could make sense for manufacturing technologies. Namely, on-tap access to technology services that are simple and don’t require a capital investment fund a small country would be proud of to deploy.

Whatever the direction of change, technology that combines accessibility, availability, and ease of adoption without lock-in will take us far, increasing our flexibility and therefore reducing our exposure to the risks associated with change.

So how do we do that?

one part right first time, but making many. What’s more we must account for occurrences on the factory floor that are difficult to replicate. Quality issues could arise from environmental changes or tools simply wearing out. Somehow, we must capture these changes, and feed them back into the design process. Manufacturers that can digitise the real world and compare it to the digital world have a unique advantage, particularly in large volume production and assembly.

A simple example of this is what Hexagon calls Intelligent Machine Control (IMC). IMC is a feedback loop that connects CNC machine control simulation to statistical quality-control software. Sensors inside the CNC machine measure changes in the end quality of machined parts, using real-time statistical process control software to determine part variance trends. The software automatically adjusts the path of the CNC cutting tool to compensate and adapt, thereby maintaining the end quality of the finished component. Automated processes like this help maintain manufacturing quality yield

rates. What’s more, production lines can run while quality checks are underway, increasing manufacturing productivity and efficiency.

Another simple and pragmatic approach is exemplified by Hexagon’s solutions for additive manufacturing (AM). The current market for AM solutions is moving fast and is extremely fragmented with numerous vendors providing multiple solutions. Achieving a clear, consistent workflow that delivers consistent results is tough.

Using Hexagon’s solution for digital transformation, SFx, as a backbone, customers can flexibly integrate their AM processes, and draw data from across design, engineering, production and inspection systems. Driving this data through system process control (SPC), machine learning (ML) and AI tools and technologies, manufacturers can incorporate better insight and automated analytics into their processes to continuously improve their AM workflows by making them more efficient, predictable and repeatable.


Getting down to essentials

At Hexagon, we believe optimised design and production, agile & efficient operations, are driven by leveraging data and intelligence, making operations increasingly autonomous as data is put to work. With closed loop processes we believe we can better orchestrate and manage quality and minimise waste by learning and adapting to changing conditions. To do this requires a new way of working.

Digital twin technology presents manufacturers with unparalleled opportunities to achieve greater quality and efficiency in the product development process. By drawing on manufacturability, production and quality data and insights in the early design process, manufacturers can improve first time quality yields, avoid delays and costly modifications when the product goes into final production, as well as optimise product and process performance.

However when manufacturing at scale, it isn’t a question of making

The key here is the idea of openness. Openness to third party systems facilitates the flexible integration of new best-of-breed tools and solutions, and helps our customers address their individual needs. The open architecture approach of SFx lays the foundation for Hexagon´s AM ecosystem which provides access to multiple technologies and capabilities relevant for developing individual AM processes.

In this way Hexagon’s smart manufacturing solutions for additive manufacturing can help accelerate the industrialisation of AM technology - generating multiple digital twins all along a digital thread at every workflow milestone, from generative design, through to manufacturing operations all the way to final product quality assurance.

However, it is important to look beyond integrating toolsets. Most traditional PLM systems stem from the need to manage mechanical design processes and facilitate collaboration between engineers. Over time, these tools and solutions have evolved to incorporate more and more capabilities, which has

been a boon to many of the companies adopting them.

If you look at modern, cloud-native product development practices, most enterprises are adopting open, flexible development systems that enable them to use the best of what’s available and drive dynamic, adaptive, autonomous systems and processes. They’re a combination of agile services, connected through APIs that enable interoperability. When we look at the future of PLM, this is what we see, not a rigid set of dogmatic ideas centred around a single source of truth and old-school ideas of process management.

In order to make this work, PLM and manufacturing-execution systems need to adapt to accommodate modern requirements. This entails not just interfacing data and information between tools on the shop floor, but also inserting a high degree of data insight, intelligence, and adaptability into that information prior to its exposure to design and manufacturing planning in PLM systems.

Equipped with more open and flexible systems, it becomes possible

to foresee mechanical product development that’s more analogous to the continuous development (CD) techniques used for software from design to production – the digital twin is nothing more than a software artifact, it just represents a physical product, so why can’t we develop it with modern and agile development ideas?

There are really six core ideas our software needs to incorporate:

1. Digitise - Digitising the physical world to mix it up with the virtual.

2. Connect – Integrating different systems, tools, and processes

3. Automate – Automating standardised processes

4. Track – Gaining visibility into what’s going on

5. Analyse – Understanding the huge amount of data in our customers’ processes

6. Utilise – Taking insights and using them, automatically

So, once we’re identified some good candidates for transformation, and we know what we can realistically achieve and how, what is stopping us really, from making a start?


How can Hexagon help?

Hexagon’s SFx solutions for digital transformation helps accelerate our customers’ digital transformation efforts by solving digitisation and integration challenges with a highly agile framework.

We believe that Hexagon’s solutions for digital transformation provide a radical new approach to accelerating digital transformation – one that is deep and comprehensive in the core capabilities

needed today, yet infinitely scalable for the future; easy to implement; and compatible with existing information and operational technologies.

We believe this so much, that we’re using our SFx framework for our own digital transformation, addressing enterprise integration, cloud orchestration, data visualisation, built-in mobility, intelligent edge connectivity, IOT and artificial intelligence.

Hexagon’s framework for Digital Transformation is proven to provide organisations with the capabilities they need for both operational & engineering excellence.

Operationally, Hexagon provides a unique portfolio that streamlines processes with a lightweight flexible app framework that accelerates existing investments in MES, PLM & ERP, enabling customers to get up and running in as little as six weeks.


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