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Although trams have matured, fuel vehicle owners will still be more inclined to fuel vehicles. How to produce models with high prices and long endurance while making a profit is a challenge for tram manufacturers.
Hexagon surveyed 416 global automotive professionals, and the majority of respondents believe that electric vehicles will not be in line with fuel vehicle prices until 2026-2028. In Europe and the United States, 36 percent of respondents believe that the price of electric vehicles will not match the price of fuel vehicles until 2028, and 47 percent are convinced that price is the biggest concern of consumers, and high prices are a major obstacle to the lack of popularity of electric vehicles.
Figure 1
Consumers expect electric vehicles to increase endurance (84%) and reduce prices (60%), but how can manufacturers balance these two demands? Enhanced endurance means investing more in batteries, but also more to reduce body weight.
Despite higher costs and lower yields due to the pandemic, manufacturers have chosen to lower prices to attract consumers (see Figure 1) and justify this decision. The survey also shows that the endurance problem is still one of the concerns of consumers, and only the use of batteries with longer batteries can solve this problem, but long batteries mean that the cost of production vehicles will be greatly increased.
Respondents believe that price is one of the biggest challenges in the transition from fuel vehicles to trams, so manufacturers need to consider how to balance the price with the cost. Analysts believe that due to the high development costs, most fuel vehicle brands are only now seeing the potential profit of electric vehicles. The only way to address the conflicting needs of lower prices, increased profits and longer ranges at the same time is to improve efficiency across the industry.
The paradoxical dilemma of manufacturing is that the number of tram buyers is low, making unit prices high; the results show that due to the low order volume of electric vehicles, buyers cannot meet economies of scale, and suppliers cannot achieve economies of scale.
Figure 2
For traditional manufacturing, improving efficiency means increasing production, and increasing production is fundamental to large foundries. But today's manufacturers who want to reduce time to market must be more efficient, and to improve efficiency, they must increase the number of parts produced, which means that if you use intelligence, or data manufacturing, you must start with the production of parts.
Many foundries have been using costing capabilities for many years, including CAD software in the early stages to assist shop floor production. Factories now require more flexible, collaborative teams that combine pre-development and post-assembly at the same time and drive data to solve problems quickly.
Successful manufacturers today are successfully reducing the time from design to production and proving the value of virtual prototyping by using simulation-intensive approaches, while their innovation cycles are shrinking. This production model helps to reduce vehicle costs while anticipating and resolving potential defects in a timely manner to avoid unnecessary expenses and time delays.
A successful example of this manufacturing principle, Valeo collaborated with Hexagon to develop a new electric drive unit, and Valeo's engineers quickly came up with multiple design concepts using software, assembled using existing components, and won the PACE Award. This approach uses a modular design that reduces development time by 7-9 months, is suitable for a wide range of applications from electric motorcycles and electric bicycles to electric vehicles, effectively reducing manufacturing costs, Valeo uses this model to reduce the time to market of citroën AMI One from 24 months to 18 months.
The most obvious benefit of having departments work together is that the development and production of the system is more integrated, but doing so requires increased supply chain collaboration and vertically integrated manufacturing.
The term "smart manufacturing" is often used to describe a variety of manufacturing processes that leverage data, and data-driven and robotic production requires the interconnection between development, production, and assembly.
Take the design and manufacture of transmissions as an example. The time to develop the gear can be calculated by using quality data, the production of parts can be started before the chip is manufactured, and the data calculated in real time can detect and prevent problems in advance. When an inevitable problem is identified, the data can identify the problem and trace it back to the material, operator, machine tool, tool, etc. that created the problem. The electronic transmission to the machine and inspection equipment greatly reduces the probability of errors compared to the original handwritten data.
Using data to predict problems and harmonize with production through statistical analysis can help bridge the gap between design concepts and product manufacturing quality.
More and more manufacturers are beginning to use the engineering cooperation model, which greatly improves the manufacturing efficiency of electric vehicle products and improves the manufacturing level of manufacturers. For example, Lucid Motors, a pure electric luxury car brand in Silicon Valley in the United States, has produced a completely new drive unit by merging various departments to work at the same time. Lucid's analysis of the electric drive as a single system and the collaboration of engineers from various departments have allowed the company to create the smallest, lightest and most efficient drive on the market. The 73 kg, 500 kW drive consists of an electric motor, transmission, differential and inverter with market-leading performance.
Arrival, a British tram start-up, is pioneering vertical production technology and robotic assembly to enable highly automated micro factories, the opposite of traditional production lines. Suppliers need to mobilize people in real time and update systems to meet the real-time changing needs of the automotive industry, which is more like the production method of software companies.
In the past, fixing design or software problems exposed during production required multiple departments to work together to locate the problem, improve the design, obtain approval, validate it, and finally return to the factory to continue production. The process can take weeks or even months — something that still happens today — but the latest approach is to use a more dynamic and often automated approach to problem solving.
In the past, you would never hear a car company say something like, "We're iterating fast," but when you consider the pace at which electric cars are evolving today, that phrase has become so apt.
Automotive manufacturing must be flexible if it is to succeed. The normality of change has been demonstrated through the pandemic, supply chain disruptions, and now suppliers are addressing these changes in a variety of ways.
Flexible manufacturing processes can accommodate changes in inspection needs due to changes in product design. This new model ensures product quality without adding additional labor, while also enabling products to be brought to market quickly.
Skoda's partnership with Hexagon exemplifies the benefits of flexibility, with the company using new robots for programming and control software that reduces programming time from days to just four hours. The company equipped the new plant with HxGN robots for autonomous inspection of equipment, while retrofitting existing production lines. The software is used in the design and inspection of vehicle components. Currently, Skoda Motors uses the software to deploy quality inspections on production lines more quickly so that they can collect production data for new cars.
The frequent retrofit requirements of electric vehicles are one of the biggest challenges for manufacturers, and since the tram is a "product" that contains both software and hardware, the production of electric vehicles requires a sound manufacturing process.
As a result, production floors and closed IoTs must be transformed for the purpose of creating collaboration and connecting manufacturing processes for rapid assembly and timely identification of missing parts. This is done on the premise that the robot and the system must be able to communicate with each other in order to detect and correct the failure in a timely manner.
The challenge for automakers is how to stay ahead of the world order in electric vehicles, both from within the industry and from the outside. Under the current order volume, if you want to meet the price concessions and the choice of more models at the same time, the traditional mass manufacturing production line must be replaced by more flexible manufacturing to speed up the time to market.