Trends in digital manufacturing at Smart Factory Expo 2018

By Jovile Bart and Matthew Skelton

Summary: 2019 is the year for manufacturing leaders and engineering managers to begin and accelerate their company’s digital manufacturing journey. The UK manufacturing sector lags behind many similar countries in terms of 4IR and digitalisation, and the world will not wait for the UK to catch up.

We visited the Smart Factory Expo 2018 in Liverpool on 14–15 November 2018 to catch up with exhibitors and see that state of the art in digital manufacturing.

The Smart Factory Expo is part of Digital Manufacturing Week, the UK’s national festival dedicated to bringing together manufacturing executives across dozens of events over four days. The festival is organised by The Manufacturer magazine, the UK’s largest industry title with 158k-strong reader community, and a heritage of over 20 years. As part of the week, four main events were separated into Smart Factory Expo, The Manufacturer MX Awards, Manufacturers Night Summit and Manufacturing Leaders Summit.

Digital Manufacturing in the UK

Mark Hughes, Regional VP of Epicor for UK & Ireland, explored the trends for today and tomorrow and shared some statistics of how UK businesses look in the global context. According to research from the Boston Consulting Group (BCG), the benefits of digitalisation in manufacturing are huge: industrial production can be 30% faster and 25% more efficient.

We learned that:

  • 1% vs 10% — Only 1% of UK manufacturing companies are “digital champions” compared with 10% globally.
  • 1% of UK firms have attained master Industry 4.0 status, compared with 5% of firms in EMEA, 19% in Asia, 11% in Americas, and 10% globally. The UK is well behind on 4IR adoption.
  • Only 1% of UK manufacturing firms have implemented Artificial Intelligence (AI) solutions although 24% see the potential.

Mark also reported significant concerns within UK manufacturing around Brexit and the possible use of 3D printing and on-demand additive manufacturing to alleviate possible supply-chain problems. The Digital Readiness Level (DRL) tool - supported by Digital Catapult - can be a useful starting point for UK manufacturers looking to assess their digital readiness.

Adoption of digital techniques for manufacturing

Over the next 3 years, many UK manufacturers are planning to increase their investments in digital technologies for manufacturing:

  • Advanced robotics: 49 % of firms are currently investing and 40 % of these will increase investment over 2019–2022
  • 3D printing: 46% investing now and 37% will increase investment
  • IoT: 44% investing now and 39% will increase investment
  • AI (Artificial Intelligence): 38% investing now and 41% will increase investment
  • AR (Augmented Reality): 26% investing now and 28% will increase investment

Digital manufacturing is already here

It’s clear that there is a wide spread of digital adoption across the manufacturing sector. Some firms have already adopted digital approaches with significant success. For example, auto giant Ford is using exo-skeleton suits for factory workers to help them lift heavy parts and reduce injury.

EksoVest is the latest example of advanced technology Ford is using to reduce the physical toll on employees during the vehicle assembly process, lessening the chance of worker fatigue, injury or discomfort [source]

On display at the Smart Factory Expo was the Mark system from ProGlove, a simple but radical innovation that helps logistics and factory workers to complete scanning and order picking more effectively whilst reducing mistakes and ensuring correct tracking of inventory.

Digitalisation for Manufacturing from Conflux

At Conflux, we offer a Digitalisation for Manufacturing service that helps manufacturing organisations to adopt effective practices and approaches with digital technology at a sustainable pace.

Conflux now offers a Digitalisation for Manufacturing service. Find out more at

We have been working recently with a UK-based global manufacturer in the pharmaceuticals space, looking at ways in which both the laboratories and the manufacturing plant could benefit from increased use of digital sensors and data aggregation/display. Through a partner we ran a hands-on workshop for managers demonstrating the practical benefits of digital sensors, and we’re now working on increasing the use of digital tools and sensors in the testing and manufacturing processes.

It is clear that with targeted adoption of digital sensors and enhanced approaches to data collection and display, significant improvements can be made in many manufacturing areas.

Digitalisation for Manufacturing from Conflux

Registration for the 2019 Smart Factory Expo on 13–14 November is already open.

What can Manufacturing & Making learn from 20 years of software development?

I recently gave a talk at the Digital in Manufacturing and Making event as part of Leeds Digital Festival 2018 reflecting on what the software industry has learned in the past 20 years that could be useful for people in manufacturing and making.

Jacquard loom from 1894 still working with “code” inputs — at Armley Industrial Museum, Leeds, UK

I’ve been working in the software industry for just short of 20 years. In that time we have seen incredible advances in digital technologies along with huge advances in software engineering and systems engineering approaches to be able to deal with web-scale systems. Here are 4 key things that I think we’ve learned in the past 20 years in the software industry that we can offer to other industries, especially those industries now adopting digital approaches like manufacturing and making.

(Slides below)

Design for change & failure — we have useful patterns

One of software’s key properties is its malleability: we can change it and re-shape it easily. This sets software engineering apart from most other engineering fields because we have come to explicitly expect change and design our software systems to accommodate not just occasional change but rapid, regular, relentless change.

This drive for relentless change in software has forced us to discover and adopt many useful patterns for working with this kind of change: service discovery, robust routing protocols, stateless scaling, search algorithms, public key infrastructure (PKI) and its related encryption patterns like public-private keys, and many more.

The speed of change enabled by software forces rapid discovery of failure modes too, along with patterns to deal with failure: fault-tolerant networking, fault-tolerant clustering and data replication patterns,

Learning 1: design for relentless change.

Iterative delivery works — Agile/Lean approaches

Iterative (not incremental) delivery can be very effective if done well.

Software is cheap to experiment with, and easy to adapt time and time again. This has made it amenable to the discovery of techniques that focus ruthlessly on early delivery of customer value: user stories, thin slicing, MVP, and so on, many of which derive from principles in the Agile Manifesto. Done well, agile and lean approaches help us to “zoom in” on the core of the problem we’re solving, without getting side-tracked in “nice to have” features and over-engineered “reusable” solutions. When we combine these value-focused approaches with the practices of Continuous Delivery and a focus on operability, we have a powerful way to deliver sustainable innovation.

Getting the thing (software, product, solution) in the hands of real users (whether at scale or at least in a beta launch) is such a key validation for our assumptions that we want to do this as early and as often as possible. In fact, we should expect to be wrong and learn from the real world. This is very far from the “genius inventor” of yesteryear, sitting in a dark room, tinkering away until the masterpiece is ready. With software we use regular real-world validation of our systems, together with rich digital telemetry, to tell us what works and what does not work.

Learning 2: frequent iterative delivery with engaged stakeholders works.

Design for version control — full digital change tracking is powerful

I think that modern version control systems like Git and Mercurial are close to wonders of the world, particularly when combined with browser-based user interfaces like Github, Bitbucket, Gitlab, etc. Version control systems for software (code, configuration, documentation, etc.) enable us to employ powerful reasoning about changes without which those changes would be incredibly error-prone and fraught with doubt. We can drive very specific automation from a change change to a single file in version control, all due to the fact that we store our specifications (code, config, etc.) as plain text files that can be parsed and interpreted by software.

Version control systems provide a rock-solid foundation for reasoning about changes.

Having experienced version control working so effectively, I cannot now imagine wanting to engineer any kind of commercial system (digital or mechanical) without using version control to store and track the digital specifications for the system: it would feel very wrong.

The speed of innovation in the software sector is underpinned by a solid foundation of richly-featured version control systems. The manufacturing and making industries can take what we’ve learned and built in the software industry with version control to build a secure foundation for specification management.

Learning 3: put every specification in version control: code, instructions, documentation.

The system is socio-technical — people and machines together

When we look at web-scale software development — many hundreds of people deploying thousands of software changes every day to live systems in just a single organisation — we see system effects that are neither purely social (human beings) nor technical (machines), but a combination of humans and machines: socio-technical. This is particularly noticeable in the studies that have confirmed Conway’s Law, originally stated in 1968 but since validated (more or less) especially with teams building software:

Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure.

This means that when we build systems we must co-design the organisation’s on-the-ground communication structures together with the “thing” we’re building. We need to work out how to engage teams in what they’re building, and allow them to be invested in what they are building; history tells us that treating people as replaceable “resources” that simply execute instructions has never been particularly effective as a strategy for making things.

Digital technologies will augment human involvement in manufacturing and making: better telemetry will enable better decisions and fewer dull, repetitive activities. For example, I was recently speaking to someone from Leeds Hackspace who was interested in using a Raspberry Pi to monitor the temperature of a fluid bath for dyeing yarn by hand: she was engaged in a very old tradition but was happy to get help from digital technologies to deal with the boring aspects (getting the temperature just right).

Learning 4: The system is socio-technical: people and machines working together

Assembly Conference 2018 — the conference for digital in manufacturing and making — will take place on Tuesday 02 October 2018 in Leeds. Tickets are now on sale:

Slides from my talk on 16 April 2018: