The Manufacturer MX Awards 2016 winners announced
Yesterday, the very best of UK manufacturing gathered at the Vox Conference Centre in Birmingham for an evening of celebration at The Manufacturer MX Awards 2016.
The annual occasion is dedicated to encouraging and promoting competitive manufacturing in the UK, and celebrating the very best in the industry. It is the culmination of an intense two stage, four-month judging period, which included benchmarking factory site visits covering over 10,000 miles with a panel of over 50 hand-picked, experienced judges. This year the judges included: Steve Whittle, Head of Business Intelligence, Rolls-Royce; Robert Carr, Oxford Instruments; Gil Woodward, Manufacturing Manager, Accolade Wines; and Archie MacPherson, CEO, WMG Centre.
Supported by 15 industry sponsors, including NatWest, which has sponsored the event for ten consecutive years, the celebration attracted manufacturing business of all sizes engaged in a diverse range of activities, with 2016 seeing more than 50 manufacturing businesses represented across 15 award categories.
A spokesperson from Dura Automotive winners of the overall award Manufacturer of the Year said: “We are thrilled to have been selected for Manufacturer of the Year 2016 and particularly against such robust competition that was clearly demonstrated by the shortlisted companies. Winning what has long been recognised as the ultimate UK industry accolade will undoubtedly help us in securing further contracts in the future. This is a true testament to all the hard work our teams have put in over recent years.”
Compered by Comedian Rory Bremner, a fantastic evening was enjoyed by all, with Hennik Group CEO Nick Hussey saying, “The Winners have demonstrated a very clear strategy, superb employee engagement through skills development and training, hugely effective customer focus and an overall level of manufacturing excellence which is truly world class. They are an exemplar of the wonderfully diverse and vibrant UK automotive manufacturing sector. They should be very proud.”
Philippa Oldham, Head of Manufacturing at the Institution of Mechanical Engineers, said: “The TMMX Awards showcase the amazing vibrancy and talent in UK manufacturing and I’d like to congratulate all of this year’s winners. Manufacturing is at the heart of the UK’s economy, and these awards not only recognise outstanding achievements, but also help drive improvements in business practices of all the companies involved.”
Richard Hill, Head of Automotive and Manufacturing at NatWest, headline sponsor for the event, told TM: “A big congratulations to the team at Dura Automotive on their success at this year’s awards. Manufacturing remains a key focus for us and we’re delighted to be continuing our support of The Manufacturer MX Awards. The awards programme and the gala ceremony are an incredible reflection of the diversity, innovation and expertise that British manufacturing has to offer.
“Our team of manufacturing specialists, who are based across the UK, will continue to work closely with the manufacturing industry to help support and stimulate more of this great work.
“I’d like to congratulate all the participants, and specifically the winners, for their achievements and also for their contribution to the sector and the UK’s prosperity as a whole.”
Winners and Highly Commended are:
Innovation & Design
Highly Commended: McLaren Automotive Ltd
Winner: Xaar Plc
Partnership with Education
Winner: GE Aviation
People & Skills
Supply Chain Excellence:
Highly Commended: Coty Manufacturing UK
Through-life Engineering Services:
Leonardo Airborne and Space Systems
Coty Manufacturing UK
Young Manufacturer of the Year
Andrew Williams, Vaillant Group UK
Apprentice of the Year
Andrew Batsford, Stadco Ltd
Gareth Humphreys MBE
World Class Manufacturing
Leadership & Strategy
Highly Commended: Coty Manufacturing UK
Hayward Tyler Group Ltd
Hayward Tyler Group Ltd
Manufacturing in Action
McLaren Automotive Ltd
The Manufacturer of the Year Runner Up:
The Autins Group
The Manufacturer of the Year 2016
Follow @ManufacturingGL and @NellWalkerMG
5 Minutes With PwC on AI and Big Data in Manufacturing
Please could you define what artificial intelligence is, and what Big Data is?
AI is the ability of a machine to perceive its environment and perform tasks that normally require human intelligence, and it’s a whole field of different technologies, techniques and applications.
Big data is a set of tools and capabilities for working with, for processing, extremely large sets of data.
How does AI and Big Data work together?
Big data is just one of the enablers of AI, though as we see increasing volumes of data, it’s one of the most important
How can this be applied to a manufacturing setting?
Broadly speaking, there are many benefits of AI, and the use of data, which include reducing costs, minimising human error, and increasing productivity and efficiency. The important thing to consider is any setting - for the use of any technology - is what is the problem you are trying to solve? Be it merely automating repetitive tasks or to reinventing the nature of work in factories by having humans and machines collaborate in order to make better and faster decisions.
Why should manufacturers use AI and Big Data when adopting smart manufacturing capabilities, what is the value for manufacturers?
One view is, again, the economic benefits of AI, which come in manufacturing as a result of:
1. Productivity gains from automating processes and augmenting the work of existing labour forces with various applications of AI technologies.
2. Increased consumer demand due to the increased ability to personalise and tailor manufactured products, along with higher-quality digital and AI-enhanced products and services.
Manufacturing (and construction industries) are by nature capital intensive, and in our 2018 report, “The potential impact of AI in the Middle East,” we estimated that the adoption of AI applications could increase the sectors’ contribution to GDP gains by more than 12.4% by 2030.
How can AI and Big Data help manufacturers to evolve in the Industry 4.0 revolution? What about those already looking at Industry 5.0?
It’s really about the investment you make now, in order to futureproof your business.
We typically see two broad strategies or approaches to the adoption of AI. There are things that we can do immediately, without any recourse to Big Data - which is to adopt technologies we describe as Sensing, those involving computer vision, for example. There are plenty of use cases where these can be used immediately in manufacturing, such as for automatic fault detection. However, there is a longer term play which requires investing in data - getting the right collection mechanisms in place, storage, data governance, Big Data capabilities etc - in order to develop increasingly valuable machine learning driven AI use cases. This is absolutely necessary for long term adoption success.
What is the best strategy for organisations looking to realise the value of AI and Big Data in manufacturing?
AI and Big Data are only one part of a successful smart factory. The organisations that lead on AI adoption are those who have already made the most progress in digitising core business processes. In order get ahead in using AI solutions at scale, there are a number of technology investments and organisational decisions to be made, including:
1. Digitising processes ultimately leads to improved ability to generate data, and in the manufacturing setting - with many 100s of sensors generating 1000s of measurements in real time, the result is Big Data. Data is key to building AI so reliable and accurate data acquisition, management and governance are key. The production line and factories play a critical and direct role in the data-acquisition process.
2. AI strategy, both long and short term, begins with the use cases, the business applications. Manufacturers need to ask where they want to use AI and gather these use cases together and prioritising projects based on a balance of expected impact and complexity of implementation.
Of course, in addition to technology and business processes, people are at the heart of any successful technology adoption. AI teams need to be composed not only of data scientists, also data engineers and solution architects to enable their work, data stewards to ensure accuracy, and increasingly so call “Analytics/AI translators” who are able to communicate with business leaders and technology experts. Culture is also key, and manufacturers need to enable a data and AI-driven culture, building trust in data and algorithms by educating their workforce about AI and its capabilities, how best to extract value. It’s not just the positive of course, but also the risks and limitations, as these when encountered without expectations having been set, can significantly impact willingness to invest.
What are the challenges when it comes to adopting AI and Big Data in manufacturing?
has shown that one of the major challenges to implementing AI is uncertainty around return on investment (ROI). As I said, there is significant investment required for a long term data and AI strategy to be successful, and expectations around the time to see tangible returns must be set realistically.
Many companies also struggle with the data side: collecting and supplying the data that an AI system needs to operate, and ensuring that it is accurate. Again, this speaks to the bigger investments required in digitisation.
Some of the main challenges for manufacturing companies with implementing AI at a scale from our research include:
- 40% → Technologies not mature
- 40% → Workforce lacks skills to implement and manage AI
- 36% → Uncertain of return on investment
- 33% → Data is not mature yet
- 32% → lack of transparency and trust
- 24% → Work councils and labour unions
- 22% → Regulatory hurdles in home & important markets
One element highlighted here, particularly around lack of trust, and labour unions, is that AI is typically misrepresented in the media as “replacing” workers, and taking jobs. Yes, there are efficiency gains to be made from automation, as there have been since the first industrial revolution. But we believe that Data and AI are at their most valuable when they are used to augment workers, enhancing their abilities and the products being manufactured.
Another challenge we’re starting to see emerge is cyberattacks increasingly targeting interconnected equipment and machinery in smart factories. PwC recently hosted a webcast, in cooperation with the National Association of Manufacturers in the US and Microsoft to discuss this.
What are the current trends in AI and Big Data in manufacturing?
- We see companies putting slightly more focus on adding AI solutions to core production processes such as the engineering, and assembly and quality testing
- Safety is of significant importance, with techniques adopted in protocol adherence capabilities (for example maintaining safe distance from specific machinery) being adopted in more every day scenarios for COVID-19 protocol adherence
- There is considerable interest in predictive maintenance for large machinery involved in manufacturing processes, and also supply-chain optimisation
What do you see happening in the AI and Big Data industry in manufacturing in the next 12-18 months?
Honestly, I think we’ll see a continuance of where we’ve already been going for the last 12- 18 months. AI and data are already being used in manufacturing but this use doesn’t get as much attention in the media as, say, healthcare, but the success stories are there, and they will continue as operations continue their digital journeys.