According to a recent report from Global Market Insights, the AI technology market for manufacturing is set to reach $16 billion (€14.8 billion) by 2025. But while these exciting technologies continue to prevail and gather pace across the sector to help fuel the uptake of smarter manufacturing models, achieving ‘innovation’ that delivers tangible benefits is not easy.
Often, the hype of ‘innovation’ stops manufacturers from actually adopting, and all the noise around these technologies can make it hard for leaders to understand the value proposition. In addition, whether it is operational challenges, skills shortages or regulatory compliance needs, there are many supply chain issues to overcome before organisations can drive real improvements.
Here, Richard Seel, manufacturing expert and managing director at delaware, provides insights on the technologies that manufacturers should be looking to implement, such as enterprise asset management, and how they can do so to meet their wider business and supply chain goals around efficiencies, cost reduction and market expansion.
AI
Q. What conversations are you currently seeing manufacturers have around AI?
A. Most tend to be focused on topics such as smart automation, real time decision-making and the use of analytics to support advanced manufacturing solutions, machine-to-machine communications and fully-automated systems. The emphasis tends to be on how AI will augment human experience and human expertise: it is not about how advanced technology will replace individuals per se, but rather how it can provide insights that will help to eliminate difficult and repetitive tasks through techniques such as back office automation and predictive operations. There is also a growing recognition of the benefit of integrating these technologies more quickly in order to inform decision-making and reduce risk in the current climate.
Q. What are some of the biggest barriers for manufacturers looking to implement AI into their organisation?
A. The technology in many cases remains immature. As a result, organisations may struggle with the business case and providing examples of applications where AI will be able to provide fast return on investment (RoI) that will in turn create business benefits. Also, designing, implementing and delivering these solutions requires human expertise. Very few people are available that have those skills and yet also have an understanding of the business into which they would need to implement such a solution. Taken together, these factors mean that C Level decision-makers often remain unconvinced of the real practical benefits AI will bring to their organisation and the returns they will get from it.
Q: What are some of the other supply chain challenges manufactures are experiencing that are stopping them from driving improvements?
A: The biggest challenges are often unexpected risks or unanticipated events like the current global coronavirus pandemic, leading to an uncertain business climate, which in turn makes it difficult for manufacturers to drive through supply chain efficiencies. More efficient supply chain planning and tools that deliver complete end-to-end supply chain visibility can help to mitigate risk in these difficult times.
Q: Typically, what is manufacturers’ highest priority when it comes to wider business and supply chain goals?
A: Often, it is around being more customer-centric. That can sometimes mean picking on one specific operational area and driving efficiencies across it. It could be about delivering digital platforms to enable this and bring in new apps to improve certain aspects of the supply chain whether it be in transportation, warehousing or sales and then using intelligence gleaned from the data sets collected to shape business strategy. Improving supply chain efficiency and agility in this way may be especially beneficial to manufacturers in the current climate. It is important here to take bite-sized chunks of the data and use the insight from that to address specific issues rather than looking to do too much, all in one go.
The overall focus for the improvements should be on areas that impact the bottom line like productivity efficiencies, faster delivery times, reducing costs of labour and the delivery of higher quality goods, or improving order accuracy and traceability; health and safety and security.
The current crisis also has brought in a more urgent need for efficient supply chain planning and visibility. AI can play its part here in making the supply chain agile and efficient and to make quick changes to address the need for delivery speed and the rapid roll-out of new projects over the short-term.
Q: What are the two most common technologies you are seeing manufacturers looking to implement?
A: We are seeing manufacturers looking to implement real-time digital platforms that provide information from data warehouses, associated reporting, recruitment decision-making; connecting applications to tools, machines and people. In light of the current Coronavirus outbreak, the overall visibility this provides is especially key.
A lot of manufacturers are also looking to use the information they have got in a more effective way. To this end, they are developing reporting apps to provide real-time analysis that supports faster and smarter decision-making. That is often associated with the roll-out of the Internet of Things (IoT), connecting people and devices and tools across a network to provide insight to support decision-making. Manufacturers increasingly see the benefits of this kind of approach, which often necessitates lower levels of investment than other technology-based projects. In contrast, areas such as autonomous and collaborative robots require a large capital investment and many manufacturers are therefore still reluctant to take the plunge, even where benefits are achievable.
Q: How do these technologies help them to meet their wider business and supply chain goals?
A: Their wider goals are typically around improving productivity and increasing efficiency as well as delivering a quality end product. These technologies can help by ensuring that manufacturers have information quickly to be able to adjust the process in real-time and improve product quality.
Q: What common mistakes are manufacturers making when implementing new technology into their organisation?
A: They concentrate too much on the technology but then fail to invest sufficiently in change management, consultancy, and training and support. In short, they don’t focus enough on the ‘people’ element. They don’t think fully about how to introduce the technology, train employees in how to use it and upskill them. Often, in contrast, they implement the technology and as and when it goes wrong, they blame the systems. Another area which often lacks is the provision of good project and technology management. We frequently also see insufficient testing of new technology before it is introduced. In short, there is a need for more preparation from the outset into how best to implement the technology and deal with the change management issues.
Another common mistake is that manufacturers often expect a very quick RoI from new technology investment and this is often unrealistic. They don’t often set out explanations of how monetary benefits will be achieved from new technology. Very rarely is a granular financial benefits case put in place. Many manufacturers don’t really factor in the current employee base and how they are likely to work with new technology.
Q: What are some of the key tips you would offer to organisations implementing new technologies into their business?
A: Before implementing any new technology it is critically important that organisations have got together a strong business case for its introduction. They need to be crystal clear on what the granular benefits will be. Remember too that a lot of incremental changes can typically be made to the existing technology solutions and processes of businesses that will reap significant benefits without introducing new technology. They need to fully exploit existing solutions and the data they have got. It is also important, of course, to ensure that any data used is accurate and of the highest quality.
AI does have an important part to play of course but it may often best to implement it on small projects first using existing data and building proofs of concept to demonstrate how it can quickly deliver value.
Q: Looking ahead, what are some of the new technologies we can expect to see in broader use across the supply chain?
A: Key technologies that are often discussed include blockchain traceability, and 3D printing of spare parts in regulated industries such as aerospace and defence and medical. We are also likely to see greater use of robotic automation and autonomous vehicles in the future. There is also a big opportunity to introduce more virtual reality into the manufacturing process as well as making wider use of digital twins. To make all this innovative technology happen, however, significant investment is required, as well as commitment to establishing a clear business case.
Manufacturers must carefully analyse and test technologies before they implement them commercially. The rollout of 5G wireless technologies also present opportunities for manufacturers by providing higher data rates, faster throughput and capacity for more devices.
Richard Seel is managing director of delaware.
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