Stefan Hollaender, Managing Director EMEA, Formlabs
Currently, the main pressures that are driving innovation in assembly methods are energy, speed and labour costs. The rise of 3D printing is challenging the traditional methods of mass manufacturing, and offering solutions to these by making product assembly processes much more efficient.
For example, the ability to create prototypes with 3D printing means that product designs will be brought to fruition much faster. Manufacturers will increasingly use advanced materials to test concepts, communicate requirements, and validate designs for manufacturability. Additionally, when using 3D printers, there is the opportunity to test manufacturing methods, such as over-moulding, before committing to a design process, which can significantly reduce wasted material, and reduce costs. As sustainability concerns continue to impact on UK manufacturing, we see small-batch prototyping being a key consideration in factories of the future.
But it’s not just product development that can be improved, but the factory line itself. We expect that an increasing number of UK manufacturers will bring jig and fixture production in-house as, using 3D printing, there are no minimum order quantities, no toolpath programming, wide material selection, and low capital equipment costs.
As the UK enters a period of uncertainty, we also predict that a lot of companies will look for ways to shorten supply chains and bring their operations closer to home. 3D printing will become a big part of this shift - by bringing the prototyping of products and the production of jigs, fixtures, and tooling in-house, manufacturers won’t have the need to outsource parts to an external vendor. Not only will this improve operational agility and dramatically reduce costs, but can give UK manufacturers the peace of mind that there will be minimal disruption to their operations as the country goes through a period of change.
Jenny Oldfield, CEO, Veritas Commercial Services
Technology will, without a doubt, continue to have a massive impact on manufacturing.
The availability of better Enterprise Resource Planning Systems (ERP) and cloud technology, means that manufacturing businesses are no longer tied to older clunky accounting systems of the past. Nowadays, they can embrace new technologies that enable automation of many of the menial paperwork-based tasks previously undertaken by office staff, such as quotation sign off (e-sign off software becoming increasingly popular).
When a process is enabled by a piece of software ‘talking’ to another piece of software without human intervention, efficiency increases, and costs reduce. Both beneficial to any business. It allows time to focus on the more human elements of work, like complex decision making.
Procurement by larger companies is becoming more and more automated, with new portals being adopted as a method of communication, which will continue rapidly. The manufacturing sector is going to be impacted by these changes and will need to adopt the finance systems to cope with the requirements of electronic data interchange (EDI), for example.
Likewise, technology is transforming the ways of working for SMEs. For instance, the Microsoft 365 environment actively encourages businesses to automate processes wherever possible, giving them the freedom to bolt on apps to their infrastructure and even develop new ones when a suitable one does not exist. This means finance departments can integrate better with the business to ensure financial transactions are speedy and accurate.
Accuracy and speed in sales invoicing are fundamental to getting paid quickly by customers. We are already seeing the impact of change in customer procurement processes. If a business doesn’t follow their customer’s procurement process, the impact on cashflow is immediate. Part of the ‘know your customer’ process needs to incorporate a thorough understanding of the procurement process and this needs to be considered in the commercial negotiations. They need to have the technology to meet the customers’ needs.
The flow of paperwork from purchase of raw materials though to getting a sales invoice paid will be automated. AI will play a large part in validation of data, further minimising human intervention. Utopia in cash flow management is, of course, that invoices are paid immediately on validation without the need for credit terms because there will be no debtor or creditor management required by a company i.e. the company sells enough to pay for what they buy. So, no creditors and no debtors. But this is unlikely to happen by 2030.
AI will also influence credit risk decisions. To a certain extent it already does with the credit reference agencies analysing the various sources of payment history data from businesses and using algorithms to give opinions on a business’s ability to pay.
We see this increasing as the volume of business transactions (and therefore measurable behaviours) moves into environments where it can be captured and analysed.
The working week is likely to be very different, with increasing support functions being physically remote from the manufacturing process as people adopt to work from home / more suitable office locations.
Heightened connectivity through technology means a business no longer needs a complex infrastructure for their support teams. VoIP, cloud hosting and increasing user knowledge of IT is changing all of that.
Jonathan Plummer, Managing Director, Electronic Manufacturing Solutions
In recent years, electronics manufacturing has stepped up thanks to the emergence of a range of innovative and disruptive technologies. So far in 2019, we have already seen a sharp rise in developments such as the Internet of Things (IoT), Artificial Intelligence (AI) and 3D printing – which are set to dominate the manufacturing industry in the upcoming months.
These developments have led to advancements in automation and equipment maintenance – transforming the production process and increasing the speed and efficiency of operations. We take a look at four of the major trends to peak in 2019
1.Leveraging the Internet of Things for real-time insights
There are currently an estimated 27 billion connected IoT devices installed worldwide – a figure that is projected to increase to approximately 75 billion by 2025. Thanks to IoT, almost every surface within the factory can be transformed into a sensor and collect vast amounts of data. This data then provides manufacturers with crucial real-time insights and updates – allowing them to optimise operations and address issues before problems arise.
So, it is no surprise that manufacturers are increasingly turning to IoT products to make informed strategic decisions, increase profitability and efficiency, improve safety and to meet compliance requirements. Over the next few months, we will likely see improved sensors and the rollout of 5G connectivity to feed this ongoing expansion of IoT.
2.Keeping production on track through predictive maintenance
For any manufacturer, ensuring all equipment is functioning optimally is a key priority, as a breakdown could prove incredibly costly both in terms of repairs and loss of productivity. Predictive maintenance technologies use a number of performance metrics to monitor equipment while it is in operation – meaning there is no loss of production due to equipment shutdown. Using IoT, these technologies then automate the data collection process and allow manufacturers to gain a better understanding of their systems and predict when they will fail.
In the next year or so, manufacturing is therefore likely to see widespread adoption of these predictive technologies, which could help significantly reduce maintenance costs, extend equipment life by years and minimise unplanned outages.
3.Using assistive technologies to improve innovation and productivity
Advances in assistive technologies have allowed manufacturing to become more intelligent than ever in 2019! For example, manufacturers can use Virtual Reality (VR) or Augmented Reality (AR) software to test different product variations during the design stage or before they go into the development process.
Both AR and VR can also improve a worker’s field of vision and show them how to perform a task and correct mistakes in real time – making it possible to quickly and effectively train unskilled workers, reduce inspection times and enable tasks to be completed faster.
Equally, AI is extremely effective at detecting and classifying problems as they arise and providing instant, timely solutions – helping to improve operations, eliminate defects, increase profitability and reduce lead times. Throughout the rest of 2019 and beyond, these assistive technologies will likely continue to have a positive impact on manufacturers.
4.Making production cheaper and faster with 3D printing
3D printing makes rapid prototyping possible, allowing manufacturers to produce items on demand (potentially even on the same day as requested!) rather than having to manufacture and warehouse them. This is a quicker and highly cost-effective way for product designers to test and troubleshoot products.
3D printing has already been embraced by the automotive and aerospace manufacturing industries. But over the coming months, we are likely to see 3D printing expand further into other sectors such as electronics – where it will help to make the manufacturing process cheaper, better, stronger and faster.
It’s an exciting time for electronics manufacturing and these are just a few of the trends that will continue to grow in 2019. But those companies that can take advantage of them will benefit from faster product development times, shorter product life cycles, increased speed to market and the agility to respond to immediate fluctuations in demand.
Mike Beason, distribution director, Anvizent
Manufacturing organisations are much more productive than they were in the 1980s. Investments into robotics and modern ERP, as well as material requirements planning systems, have helped drive tangible change in the sector and enabled revenue and margin growth. But just how many more efficiencies can be pushed out through conventional approaches? With data being one of the most valuable resources in the world, it will surely play a significant part in the future of manufacturing. Modern manufacturing companies are drowning under the weight of the data they generate, but most have no unified way of accessing it usefully in real time.
The UK Treasury published a discussion paper in August 2018, showing the potential impact of data on the UK economy. The economic value of data: discussion paper shows that firms adopting data-driven decision-making can have 5-6% higher output and productivity. The European Commission stated that ‘even limited use of big data analytics solutions by the top 100 EU manufacturers could boost economic growth by an additional 1.9% by 2020.’
The future will see the real time analysis of the plethora of data that exists within an organisation to obtain better insight into day to day operations. But manufacturers will be able to do more than that with a high degree of accuracy previously unavailable to them.
Traditionally, the information that manufacturers gain from their data is either descriptive, showing what has happened in the business, or diagnostic, showing what is currently happening. For example, manufacturers will track how many items they have made and shipped over the past month. But we’re moving towards an era where data can do so much more.
Using an advanced intelligent analytics system integrated with the ERP and operational systems, manufacturers can run predictive scenarios based on historic trends and information. This allows organisations to see how different distinct areas of operation — staffing costs, stock prices, logistical challenges, customer segmentation and purchasing patterns — might change. It also shows seasonal variation, and the effects of strategy changes that place specific demands on the manufacturing and the supply chain. Not only that, intelligent analytics at this level can be prescriptive and show manufacturers what they should do to achieve a desired outcome. For example, if a business wanted to reduce prices by 10% an advanced system would be able to predict the effect this would have on sales, required stocking levels, staffing, logistics and raw materials. Being able to use data in this way makes creating tangible future predictions a real possibility for manufacturing in the future.
Jason Chester, Director of Global Channel Programmes, InfinityQS
“What does the next ten years have in store for UK manufacturing?” It is an interesting question, and the one thing I am sure of is that, well, I am not really sure. As Nils Bohr, the Nobel laureate in Physics once quipped, “Prediction is very difficult, especially if it is about the future!” At the time of writing, the Brexit debacle continues, and we are still no clearer to understanding if we will eventually leave the EU or not, or if we do, whether that will be with a deal, no deal or some other deal!
With such outstanding uncertainty to the most fundamental decision impacting the UK in recent history, trying to predict what the next ten years will have in store for UK manufacturing from an economic perspective against that backdrop is going to be nothing short of pure guesswork. We simply must resolve the Brexit conundrum before we can make any sane attempt to assess the potential future impact on the manufacturing sector.
An area where there is far less uncertainty, in my opinion, is in how manufacturing is done. The role of technology in manufacturing automation has dominated the sector for the last few decades, but in the future, technology’s greatest impact on manufacturing will be on optimisation. The widespread adoption of industrial digitalisation across the shop floor, will move manufacturing towards an information-centric activity.
As new technologies emerge and nascent technologies mature, their convergence will give rise to truly smart manufacturing and smart supply chains that will radically transform the industry. However, this will be both an opportunity and a curse, as the liberalisation of manufacturing will create highly competitive and fluid global markets with a much lower barrier to entry in almost every sector. It will simply be the survival of the fittest.
This will be the single biggest ‘thing’, with all of the associated challenges and opportunities that will impact on manufacturing over the next ten years and beyond. To quote Amara’s Law (coined by Roy Amara): “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run." In other words, we are often disillusioned by the hype surrounding everything ‘Industry X.0’ now and, as a result, fail to recognise the seismic impact these technologies will have a decade from now.
Venkat Nandikolla, Global Head of Manufacturing, Mindtree
Machines came into factories in the 1800s and robots have been in existence in the shop floor for many years. Now we are getting into the next stage of intelligent automation where Artificial Intelligence (AI) is beginning to work side by side with humans in different ways in every sector.
The manufacturing industry is going through this change in trying to adopt AI from shop floor all the way to the top floor and this will result in more changes in the next 10 years than seen in the last 20 years. We can see a glimpse into the future in the way Internet of Things (IoT) and smart manufacturing are enabling hyper-personalisation aided by new levels of automation. Big data and analytics are converting traditional manufacturers into smart factories with digitally-orchestrated factory floors.
All this is feeding into a few real, here and now use cases to enable and expand on the usage of AI. This is driven by data becoming all pervasive as data siloes are breaking down gradually as manufacturers are coping with the changing demands of their customers and new competition which is breaking the barriers of what’s possible in every part of the manufacturing value chain. The potential of AI to disrupt, transform and rebuild businesses is also felt in the C-Suite in the manufacturing industry.
Recently, we revealed the findings of a recent survey we conducted on AI usage across enterprises. The data was gathered from 650 global IT leaders, including respondents from the manufacturing sector. Our study found most businesses are well underway with AI experimentation, but many still lack an understanding of the use cases to deliver business value and the data infrastructures for making AI a success across the enterprise on a sustainable basis.While AI can deliver business benefits, a majority of enterprises have yet to find a formula for repeatable success. Out of all industries surveyed, the manufacturing industry was one of the top five industries gaining value from AI.
To thrive in the digital age, Manufacturers must also constantly refine their understanding of how AI will give them a competitive edge and deliver real and measurable business value to maximise their investment in these disruptive and powerful technologies, while also accepting the fact that intelligent automation is not an attempt to make humans redundant in the workforce. Instead, it is there to strengthen and complement human capabilities.
Gary Brooks, CMO, Syncron
Servitisation will become a major component of OEMs’ business over the next decade. This shift - where organisations transition from strictly selling products to selling products-as-a-service - has been discussed for some time but is far from being an established business model. Moving away from the traditional break-fix service model, where products are repaired after they have already broken down, to maximised product uptime requires the whole business logic and incentive structure to change dramatically and will require OEMs to redefine the way they operate and serve their customers.
The demand for continuous service of products is being driven by the customer. In research Syncron undertook at the end of last year with Worldwide Business Research, nearly 100 percent of end users indicated they want to see more service agreements from OEMs that offer maximised product uptime. There is a clear gap between customers’ increasing demand for continuous service and manufacturers’ ability to deliver it, with only 33 percent of OEMs offering this type of service contract today.
Manufacturers must invest in the technologies and infrastructure that will support the new service model: IOT, AI, sensors, machine learning, plus the software that can analyse the data and optimise the service supply chain. The research did illustrate manufacturers’ desire to close this gap with more than half planning to make AI and machine learning a major investment, while 90 percent intended to invest in predictive analytics within the year.
Even with the new wave of IoT enabled products break-fix service will never completely go away. Large, durable goods such as automobiles, heavy equipment, industrial machinery, etc. are built to last, with some product lifespans reaching up to three to four decades. Obviously, products that were manufactured and sold years ago are not equipped with IoT-enabled parts, but still need to be repaired and maintained. And there will always be unforeseen accidents with smart-enabled products. The best approach manufacturers can take is to simultaneously optimise the service supply chain for break-fix service while simultaneously deploying new product-as-a-service business models.
In ten years’ time we can expect that OEMs will no longer report on the number of new products sold, or even service parts revenue. They will in fact follow the path many SaaS companies have taken, reporting on recurring revenue from subscription-based services. Customers will subscribe to their equipment much in the same way as they do their Netflix subscription, paying for output and value. OEMs must take a much more comprehensive look at their operations and invest in technology that can help them manage the real-time service needs that arise in a servitisation-centred world.
Jeanette Mifsud, Manager, Product Marketing, Winshuttle
Data management, or lack of it, is likely to have huge implications for the UK manufacturing sector over the next ten years. Poor quality product data is a big issue and the problem is only set to intensify as companies launch more products faster than ever to keep pace with rapidly changing consumer demand.
The implications of poor data management in manufacturing are costly—both in terms of hard costs and the costs associated with erosion in brand trust. The impact of bad data shouldn’t be underestimated. For example, someone enters the incorrect unit of measure when setting up a new product. Thisresults in the products, in reality, being heavier than the system used to calculate trucking. When the truck reaches a weigh station at a border, the mistake is realised, and the truck is turned around—costing thousands in wasted time and damaging the company’s reputation. Even a small mistake in product packaging data, such as the omission of allergens, can have costly and dangerous consequences.
Typically, we see three main reasons why data management is such a challenge: Firstly, too few organisations take a proactive stance to data quality—i.e., having technology and procedures in place to ensure that data coming into the system is right from the outset.
Secondly, there is sometimes a lack of ownership within most organisations with IT and the lines of business unsure as to who is responsible for data quality.
Thirdly, as the Internet of Things and social media platforms expand along with traditional data sources, even the best-intentioned IT and data teams can’t keep up with policies and technology to ensure that new data coming into their systems is high quality, and that cleansing of their existing data happens regularly.
Making meaningful improvements in data quality requires a big commitment in time and resources and buy-in from senior leadership. Serious change requires a combination of the right organisational structure, the use of effective technology, and ownership and accountability of the data. Technology can help make all of this easier and faster, but it’s an enabler and not a set of silver bullets. In order to prepare for the future of manufacturing, the culture of the business needs to change to make data quality a priority.