May 17, 2020

Comment: Strengthen logistics today to operate the smart fleet of tomorrow

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Jeff Butler, Product Manager, ...
6 min
The logistics industry has to do more to prepare for the future of smart fleets
Despite the hype around smart fleets and autonomous vehicles, Jeff Butler, Product Manager, Logistics, Products & Solutions from Quintiq argues the...

Despite the hype around smart fleets and autonomous vehicles, Jeff Butler, Product Manager, Logistics, Products & Solutions from Quintiq argues the fleet and freight sector still has a lot of ground to cover

Barely a week goes by without a new development in the world of autonomous vehicles. The technology is accelerating at an amazing pace, and vehicles have already hit the roads. Trials of wireless trucks travelling in convoy across Europe have been a success, and manufacturers like Mercedes Benz are creating concept commercial vehicles such as the Future Truck 2025. Despite concerns around safety and legal responsibility in the event of an accident, almost all major vehicle manufacturers are preparing to launch competitive products - it is clear the autonomous vehicle revolution will become a reality.

For executives in the fleet and freight sectors, smart fleets of autonomous vehicles may seem some way off, but progress in making such vehicles technologically and economically viable is further along than one may think. California’s Interstate 10 highway, for example, has seen autonomous trucks transport Frigidaire refrigerators 650 miles between a distribution centre and warehouse since October 2017.

Of course, there are still drivers in the trucks, but this demonstrates the technology’s real-world application. This trial is not alone, of course, with the likes of Waymo and Uber testing autonomous vehicle technology. In August 2017, the United Kingdom’s Transport Research Laboratory announced it had received £8.1m to conduct trials with semi-autonomous trucks on major roads by the end of 2018.

While smart autonomous fleets offer a plethora of benefits, McKinsey & Company predicts this technology is still a decade away from becoming mainstream – so why should the logistics industry get excited now? The truth is technologies such as supply chain optimisation and control, which will be essential to underpinning smart fleets, can still transform the efficiency of operations now.

Smart fleets and autonomous vehicles will both generate and require massive volumes of data. Whether transmitting information from on-board sensors, or downloading ultra-high resolution maps, an organisation’s systems need to be able to receive, understand and respond to this data in real-time. However, fleet or freight operators already require this capability, often needing to respond to a range of omni-modal transport challenges in the face of unforeseen disruptions. Any firm operating without real-time capabilities is instantly at a disadvantage when competing against more tech-savvy competitors.   

DHL Germany is a great example of how working to build responsive connected technology platforms brings real benefits now. DHL’s SmartTruck technology has used dynamic route planning operations to reduce CO2 emissions; increase dispatch productivity; improve service quality; and enable greater precision in pick-ups and deliveries. DHL reduced its tour duration by eight percent and decreased mileage by a further 15% using this technology – for any logistics company these are huge benefits – all without a single autonomous truck in sight.

If organisations are serious about smart fleets, and eventually adopting autonomous vehicle technology, then the foundation work should start now. By doing so, fleet and freight sector organisations stand to realise immediate benefits, like increased operational efficiency and greater sustainability, while also implementing a robust platform capable of supporting smart and autonomous fleets in the future. There are three key technology areas to focus on in building such a platform:

The Internet of Things (IoT)

Whether it’s advanced sensor technologies and data capture or predictive analytics and automation, the effective use of IoT delivers data-driven insight so organisations can respond in a timely manner. In fleet and freight organisations, this means identifying issues like faulty processes, vehicles or refrigeration units, generating alerts, then deploying resources to immediately rectify the problem.

IDC estimates human error and employees not fully understanding their jobs cost US and UK businesses approximately £18.7 billion every year. By removing many manual processes and automating repetitive tasks, IoT can eliminate delays and reduce the chance for human error while empowering staff to focus on higher value initiatives.

The challenge with implementing IoT is having a connected platform capable of capturing and analysing a constant stream of updates from hundreds, even thousands of data-points. Simply capturing and storing and looking backwards at the results is not good enough – rather have a supply chain planning and optimisation solution capable of delivering robust KPI-driven operational planning that analyses the IoT data to drive predictive and prescription analytics.

Real-time decision-making

Split second agility is key to delivering effective logistical operations. Having planning, scheduling, tracking and customer facing systems that operate in real time is the only way to deliver such agility. In addition, automation is impossible if the data used to power it is not reflective of what is happening in real-time.

Early this year, HCL Technologies revealed almost half of European businesses experienced headaches with data silos. Ultimately, all data sets and systems need to be able to talk to each other – and do so in real-time as opposed to in batches that inevitably lead to delays that impact service standards. Data can now move between systems and can be brought into a cycle of continuous optimization, providing customers with a better experience that also aligns their demand with a supplier’s production capability.

Whether organisations adopt autonomous vehicles or not, supply chain planning and optimisation solutions can help make informed decisions on where and when shipments need to go, on what vehicle, and then revise plans as they get real-time updates on route progress, traffic and weather conditions or road closure. Leveraging Artificial Intelligence, logistics managers can begin to deploy self-learning supply chains capable of automating and managing less critical tasks, which means they can focus on more complex issues associated with running a smart fleet.

Mobile connectivity

Through the European Commission’s 5G Public-Private Partnership, 5G networks will become a reality across Europe by 2020 and there will eventually come a time where mobile broadband will be available almost anywhere. With 5G networks improving the accuracy of location-based tracking, vehicle monitoring will also become more accurate – even in more remote locations.

For the logistics industry, 5G will better enable time-critical process control, factory automation, remote control, enterprise communication and help smart fleets exchange information in real-time at faster speeds. While 5G is expected to increase the sharing of sensory data to help improve situational awareness and accelerating the progress of autonomous vehicles, organisations need to ensure planning and scheduling platforms can accurately capture and analyse the rapid influx of data being generated in a way that is meaningful.

Each of these three areas can fundamentally affect the performance of any business moving a large fleet or freight operation. The prospect of replacing mission critical systems is not an easy one, but it is an unavoidable step if businesses want to remain competitive and relevant in the future.

Tomorrow’s problems can be answered today, and this preparatory work can bring immediate benefits. Many companies are already on their journey, implementing real-time, connected systems, and gaining the competitive advantage – if they have not done so already.

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Jun 13, 2021

Engineering skills gap challenges UK electric vehicle market

Yvonne Paige-Stimson, Global P...
5 min
Yvonne Paige-Stimson, Global Projects Director at Hexagon Manufacturing Intelligence on how the engineering skills gap is challenging the UK’s EV market

Original equipment manufacturers (OEMs) are hurrying to design and develop electric vehicles to meet the evolving regulatory deadlines. The race to do so while meeting the high consumer expectations for new products is an immense challenge – exacerbated by a shortage of key engineering skills in many national workforces.

The emergence of new engineering skillsets and capabilities needed for new automotive product introduction risks hindering the move to electrification. If unresolved this could result in failure to meet their fleet CO2 targets set for the coming decade – including the ban of all petrol and diesel car sales in the UK by 2030.

The technological transformation of cars into computers – powered by electric batteries – has created demand for a parallel transformation of the automotive engineering workforce, and a pressing requirement for new skills in software and battery engineering.

The skills of the moment

There is a huge and growing need for tech talent. In the UK alone, programming and software development jobs are growing 7.3% on average every year, and these tech roles are amongst the most in-demand jobs. Design and development engineers from either the mechanical or electronic domain, who can also programme, are the new trend. The car of the future relies heavily on programming languages such as SQL, Java, C++, and Python for development of their embedded systems and tools used in their validation. The most highly sought-after talents are those individuals who have blended to become a multi-disciplined hybrid of several specialities. 

Manufacturing also demands IT skills due to the digital transformation of the production and supply chain environments. It is now heavily reliant on Edge machine-level data processing, with cloud integration of shop-floor assets (such as robots, measurement, optical recognition, machining centres etc) all connected together with visualisation and big-data analytics. Availability of Artificial Intelligence and Machine Learning expertise becomes a limiting factor to organisations seeking to make real-time cloud-managed decisions governing quality control, predictive performance and optimise asset utilisation.

The trend to Model-Based System Engineering methods is a significant benefit to product development cost and time to market. Recruiting sufficient Computational Analysis Engineers (CAE) for system dynamics, fluids, structures and acoustics, fatigue and forming technologies, is a challenge. Computational fluid dynamics (CFD) engineers, in particular, have an essential role in EV development: to evaluate the thermal strategy for the battery architecture and integrated cooling systems, with the mission of keeping the car functionally safe and reliable in all conditions.

Closing the gap

The top drivers of the skills gap reported by employers include strong competition for skilled candidates, a shortage of applicants with appropriate qualifications, and a lack of awareness among young people of the educational routes into engineering occupations. The development goal and long-term solution is obvious: to get more people into studying engineering and widen the diversity of this talent pool. Recent UK Government initiatives are already showing some positive impact on this challenge:

  • Significant changes in GCSEs with promotion of single-science options has led to a 17.3% increase in take-up rate of Physics
  • A-level entries are on the rise for most STEM subjects – take-up of A-level Mathematics continues to be particularly high, making up 12.0% of all entries
  • High proportions of international students, especially from India and China, are studying engineering and technology in the UK, particularly at taught and research postgraduate levels (67.7% and 59.3% of entrants respectively). 

Universities are adapting to supply the future talent for the electrified automotive industry, many now offering combined degrees in mechanical and electrical engineering with dual accreditation. Degrees in Controls and Systems engineering are also gaining in popularity, teaching future engineers to work on holistic problems where there are conflicting needs and complex interactions. Given the time it takes to train a new engineer and for them to become effective in the workplace, the sector is therefore challenged to wait for this influx and mobilisation of in-demand skills to be realised.

Instead, focus turns to being ‘employer of choice’, and companies aim to attract the highest calibre new hires to staff their teams. Despite the distraction to business continuity due to COVID-19, there is no time for complacency regarding the employee culture. The most highly skilled (especially in ADAS, functional safety, system controls, CFD, electromagnetic and power electronics) can literally cherry-pick their next employer with ease, aided by the transparency of website platforms like GlassDoor and LinkedIn. 

Partnering on development

Onboarding of software and tools can significantly help alleviate the engineering skills gap – by embedding know-how, others have developed into their digital multi-physics offerings. Engineers can be assisted in getting the workflows and design rules right, creating an immediate and tactical solution to ease the product development challenges.

We can also seek collaborations and technology partnerships by working with specialist service partners locally and globally in a new ecosystem. The ability to achieve the leap to develop IP, leverage experienced resources for global teams, and offload the risks associated with finding and training the skilled engineers in-house – often gives the best of both worlds.

The unprecedented pressure on the world of engineering to develop new EV models will require collaboration on a new scale. While many countries are pushing to grow and diversify the engineering workforce, the skills gap needs to be closed now to avoid disruptive delays for the global market. As a central part of the evolution to e-mobility for our customers, the urgency of this task is starkly clear, and encouraging novel partnerships to close the skills gap will be vital to ensure our industry meets this historic goal.


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