28 Aug Smart Manufacturing for Automotive: the Key is MES
Regulations exist for overseeing the manufacture of Automobiles and Specialty Automotive Parts. In the US, there are two regulatory bodies of note: the National Highway Traffic Safety Administration (NHTSA) and the US Environmental Protection Agency (EPA). The EPA regulates vehicle emissions.
Important regulations guiding US automotive manufacturing include:
- The TREAD Act. Enacted in 2000, the TREAD Act (Transportation Recall Enhancement, Accountability and Documentation) was based on fatalities related to Ford Explorers fitted with faulty Firestone tires.
- 49 CFR Chapter V Part 573—Defect and Non-Compliance Responsibility and Reports.
- 49 CFR Chapter V Part 577– Defect and Noncompliance Notification
- 49 CFR Chapter V Part 579-Reporting of Information and Communications about Potential Defects.
- 49 CFR Chapter V Part 583 American Automobile Labeling Act Reports. This requires manufacturers to label their US and Canadian parts content.
While most specialty auto parts are not directly covered by a US safety standard, they are still subject to NHTSA oversight. First, equipment manufacturers, distributors and commercial installers cannot market or install a product that would knowingly take a vehicle out of compliance with a federal safety standard. This is called the “make inoperative” prohibition. For example, it would be illegal to market colored bulbs that, when installed, would not allow the required lamps to meet the color and performance requirements of the federal lighting standard. Second, a manufacturer must notify NHTSA when it has determined that an auto part has a safety-related defect. NHTSA will then work with the manufacturer on an appropriate remedy, such as customer notification and recall. NHTSA also has the authority to conduct its own safety investigations and may impose civil fines for failure to comply with its safety standards and other rules.
Internationally, there is a regulatory group called WP.29. The UNECE World Forum for Harmonization of Vehicle Regulations (WP.29) is a worldwide regulatory forum within the institutional framework of the UNECE Inland Transport Committee. Three UN Agreements provide the legal framework allowing member countries attending the WP.29 sessions to establish regulatory instruments concerning motor vehicles and motor vehicle equipment.
The UN Rules include provisions for safety and environmental conformance; performance-related requirements and test procedures; and periodic technical inspections of vehicles in use.
Automotive Market: OEMs and Tier Suppliers
The diagram below is a good indicator of the complexity of the Automotive manufacturing industry, worth $3 trillion, with over 1,622 businesses and employing over 2.6 million people. The Tiers alone contribute $1.7 trillion to the industry—over half of the total industry value.
Although the OEM—the final assembler such as Ford, GM, Tesla, etc. is well known, the underlying Tiers play a big part in the reliability and quality of the finished vehicle. It also demonstrates why supply chain management is so important in this industry—the domino effect of a defective part in one of the Tiers can have a devastating effect in final assembly. A single car has over 30,000 parts! So it behooves the OEM to ensure the ongoing sanctity of their suppliers through strict quality measures to mitigate the whiplash of defects in the component parts.
Smart Manufacturing for Automotive
McKinsey estimated that between 1998-2011 regulatory content and other improvements such as ESP (Electronic Stability Program/Electronic Stability Control), airbags, fuel efficiency improvement and weight reduction increased production costs by 3-4 percent per annum. More recent environmental regulations are expected to add a further 6 percent to the average manufacturing costs by 2015, and 16 percent by 2020. They also stated that the net effect has been a decline in profit per vehicle, but OEMs have been able to manage this so far (up until now) because they have been able to make efficiency and quality gains of 3 to 4 percent a year to offset.
Updated in 2016, McKinsey talked about the driving forces behind change for the automotive industry:
- New business models (mobility, data-driven services) expand the definition of car ownership and use
- Dampened growth declines from 4 percent to 2 percent by 2030, due to car sharing and e-hailing
- Segment growth of fit-for-purpose vehicles (such as for car sharing or city/high density driving)
- Autonomous driving (estimates 15 percent of new cars sold by 2030 would be fully autonomous)
- Viability of Electric Vehicles
- Multi-dimensional competition for incumbent auto manufacturers—mobility providers (Uber), technology providers (Apple, Google) and specialty OEMs (Tesla, etc.) all change the market dynamics
- Responding to disruption, manufacturers need to leverage partnerships; reshape their value proposition (not transportation, but mobility services) and drive transformational change (cyber-security, data privacy, continuous product updates/NPI)
Smart Manufacturing has been defined as the fully-integrated, collaborative manufacturing systems that respond in real time to meet changing demands and conditions in the smart factory, in the supply network, and in customer needs. ‘Smart Industry’ is a synonym for Industry 4.0 or the fourth industrial revolution, within which Smart Manufacturing fits.
The value of Smart Manufacturing for Industry is tremendous: the global smart manufacturing market size was valued at USD 215.8 billion in 2019 and is expected to witness a CAGR of 11.8 percent from 2020 to 2027 (four times greater than the growth of the automotive industry itself).
Smart Manufacturing has many components, but the basic four are to leverage/improve
- Asset Performance
- People (labor) Performance
- Information (big data/analytics) Performance
- Product (quality) Performance
Smart Manufacturing spans the supply chain—meaning that the focus is not just within the OEMs or Tiers themselves, but includes their extended value chain. Suppliers, customers, and logistics partners are all aspects of the supply chain to be considered and improved.
Smart manufacturing ‘s aim is to optimize the performance of the plant, using the technologies that Industry 4.0 brings, such as Machine Learning/Artificial Intelligence; Big Data and Analytics and AR/VR, while still embracing the earlier quality initiatives such as lean and OEE.
Smart Manufacturing is MES
The task of creating a ‘Smart Manufacturing’ foundation may seem daunting, with the various components and complexities that come with these various solutions. The simplest way to approach would be to consider a platform that contains these key technologies, allowing you to gain visibility, make knowledge-based decisions for improvements and easily integrate Industry 4.0 technologies without disruption.
Since the industry operates on such tight margins, improving supply chain performance is paramount. Automotive parts suppliers and OEMs must remove all waste out of their supply chain in order to reduce costs, whether the costs derive from the manufacturing process itself or from the extended value chain.
Complying with Good Manufacturing Practices is an important aspect; ensuring that adequate documentation is in place from incoming inspection through product delivery is one facet of visibility. They must be able to ascertain variances in manufacturing and product performance, before the product gets into the marketplace, to remove the ‘domino effect’ of a recall, and must have some type of ‘early warning’ system in place so that defective products do not get into the supply chain.
This overarching system need can be daunting, especially if you have a mix of legacy, point solutions and custom-built applications. We have touched on this before (our blog post on 6 reasons why you shouldn’t build your own software) and it holds true for this scenario.
MES (Manufacturing Execution Systems) core value proposition are that the functionality matches the industry needs. You’ll find MES specifically for food and beverage; oil and gas; or for (in this case) complex discrete assembly. Each industry has its own specialized ways of handling inventory, work instructions, labor management, equipment or asset maintenance. If the MES you choose is a mismatch, you will spend inordinate amounts of time trying to force-fit its model into your process. So look for a MES that offers:
- Robust Work Order handling
- Integration to enterprise applications, such as PLM (for the build/design data) and ERP (for the customer-centric and inventory-centric manufacturing requirements)
- In-line, at-line and off-line quality testing and SPC
- Labor management (including work instructions, AR/VR-guided interaction, certifications and e-signature capture for compliance)
- Integrated business intelligence (performance dashboards, real-time statistics)
- Underlying data platform to access real-time data coming from IoT and automation equipment
There are a host of other functionalities that a proper MES can provide. Creating a plant data model allows you to build the foundation for track/trace/genealogy, critical for quality and recall management. An ‘open’ data architecture ensures that the integrations you’ll need for visibility, system updates and interoperability with other plant equipment and systems can constantly iterate as your enterprise changes. And lastly, the right MES partner will come with an ecosystem of partners, both technology and services/consulting, to ensure your project will meet your initial goals of ‘Smart Manufacturing’ both now and in the future.