The Rise of Automotive Manufacturing and How MQTT Can Help
Automotive manufacturing is well and truly on the path of recovery from the aftermath of COVID-19. Manufacturers have realized that the best way to insulate themselves from macroeconomic factors like pandemics, wars, and others is to ensure they digitally transform their operations by adopting Industry 4.0 technologies like IIoT.
We closely studied a recent report titled The AMS/ABB Automotive Manufacturing Outlook Survey for 2023. The report discusses challenges from industries like supply chain, sustainability, electrification, costs, and other topics, and provides key insights into the adoption of Industry 4.0, Digital Transformation, and IIoT in these industries. In this blog, we will discuss the insights from this report and share how HiveMQ is positioned to support your efforts in digital transformation and implementing IIoT technologies.
Key Survey Insights
The survey provided some key insights in the areas of Industry 4.0, Digital Transformation, and IIoT. The following sections go over some of these key areas and how HiveMQ is positioned to support them.
Manufacturing Challenges
It's a well-known fact that the COVID-19 pandemic really pushed supply chain disruption very high in the list of challenges. That was evident in the previous 2022 survey, which clearly illustrated this, as 67% of respondents voted this as their number one challenge. However, for the 2023 survey, although supply chain disruption was still a major challenge (with 35% of respondents reporting this), it was not quite the dominant issue it previously was, and has been notably just overtaken by growing labor & skills shortages according to 36% of respondents.
Image source: The AMS/ABB Automotive Manufacturing Outlook Survey for 2023
HiveMQ enables reducing supply chain disruptions by bringing together both internal and external manufacturing data to a Unified Namespace (UNS) using our MQTT broker. It facilitates end-to- end visibility, automatic exception-based alerts, and predictive analytics in the manufacturing and supply chain process. HiveMQ also helps automate a number of manual manufacturing processes, enables advanced analytics tools that help factory workers be more efficient, and thereby addresses the growing labor and skills shortage.
Future Technologies
Notwithstanding the dominance of electrification and immense industry investment into EVs, battery supply chains and charging infrastructure, it was revealing that survey respondents saw the industry’s future powertrain solutions to be more varied, with no clear technological winner.
For passenger vehicles, 25% of respondents highlighted battery electric or hydrogen fuel cell hybrids as the technology that has the potential to make a major contribution, followed closely by hydrogen fuel cell vehicles (23%) and advanced batteries (22%). Notably, hydrogen combustion also received a significant response rate (11%), with a perceptible increase in interest for this emerging technology.
Image source: The AMS/ABB Automotive Manufacturing Outlook Survey for 2023
As vehicle technologies move more towards EV and electrification with either battery electric or hydrogen fuel cells, the various vehicle components have inbuilt smart sensors which are able to track the usage and other key information. This makes using IIoT easier and allows MQTT brokers like HiveMQ to capture the rich data to enable connected car use cases like enhanced customer experience, remote diagnostics, remote vehicle access, and infotainment experience.
State of the Automotive Industry
Despite some concerning economic indicators, the overall automotive industry outlook according to survey respondents was broadly positive.
In this 2023 survey, both the vehicle production and sales outlook is notably more positive than the previous year’s outlook, with 76% believing vehicle production would stay the same or increase, compared to just 56% in 2022. Likewise, in the 2023 survey, 69% believed vehicle sales would stay the same or increase, compared to only 54% in 2022, which is a notably more upbeat outlook.
Of significance was that in terms of vehicle volumes, the main constraint has shifted to demand (55%) in 2023, but in last year’s 2022 survey the main constraint was production (57%). This confirms the earlier findings around supply chain disruption in 2023 easing compared to 2022.
Image source: The AMS/ABB Automotive Manufacturing Outlook Survey for 2023
Given the easing of the supply chain and given more demand for vehicles, vehicle OEMs will focus on ramping up production of vehicles at a large scale to meet the demand. This means there would be more focus on optimizing the manufacturing process, reducing costs, streamlining product lines and increasing profitability. A highly secure and reliable movement and consolidation of the manufacturing data to enable tools like OEE, forecast planning, and predictive maintenance would be needed. HiveMQ’s enterprise-grade broker is well positioned to enable that through its ability to support high reliability, high scalability and high security in moving data from multiple manufacturing systems and consolidating them to enable IIoT use cases.
Overall Positive Outlook for Manufacturing
It is clear, based on the responses from 2023 compared to 2022, that automotive manufacturing is well and truly on the path to recovery. MQTT is playing a pivotal role in accelerating digital transformation across industries, and HiveMQ is well positioned to support automotive manufacturing customers and others in their IIoT data use cases. Check out our Mercedes-Benz customer success story of how they are leveraging MQTT and HiveMQ.
Ravi Subramanyan
Ravi Subramanyan, Director of Industry Solutions, Manufacturing at HiveMQ, has extensive experience delivering high-quality products and services that have generated revenues and cost savings of over $10B for companies such as Motorola, GE, Bosch, and Weir. Ravi has successfully launched products, established branding, and created product advertisements and marketing campaigns for global and regional business teams.