Placing inspection processes on the shop floor optimizes floor space, provides complex measurements quickly, and maintains high productivity – overcoming time and inspection room capacity challenges faced in quality control (QC).
A walk-up metrology system, made up of a vision and multi-sensor system or a coordinate-measuring machine (CMM), is adaptable and runs various measurements. Manual one-feature measurements and semi-automated multi-dimensional testing of one part or multiple parts can be taken. It decentralizes the quality and measurement function and eliminates inspection bottlenecks by placing the measurement process next to production machines and technicians making the parts, rather than requiring a QC lab. The operator or technician becomes part of the process to effectively measure parts and conform to specifications. Eliminating these issues maintains quality inspection standards, especially for vehicle components that require intricate measurement processes. Vehicle components can be inspected faster and more efficiently, while maintaining quality inspection standards. This is especially desirable for first article inspections that can cause significant production delays when the QC Lab is backed up.
“In the past, the inspection process had to be done in a separate QC lab by a quality control professional, which can require longer periods of time to inspect a part,” says Mark Arenal, general manager of Starrett Kinemetric Engineering Inc., a subsidiary of The L.S. Starrett Co. “Walk-up metrology brings the inspection process to the shop floor where a machine operator can quickly walk up to the metrology system and measure the part through a simple and repeatable process.”
Measuring automotive components such as rubber door seals, gaskets, and connecting rods on the shop floor reduces bottlenecks and enhances throughput.
“This type of system is especially critical for the automotive industry because automotive manufacturers cannot afford to lose any time or have holdups in their operations,” Arenal explains. “Walk-up metrology greatly speeds the overall process and offers maximum flexibility.”
Using a walk-up metrology system, such as the Starrett HVR100 Flip, users can place a part on the system and the program optically measures it to determine if it meets specifications. The system, which can be used in a vertical or horizontal orientation, provides automatic part and multiple-parts recognition to measure specific geometric points. Once a part is inspected, the HVR100 will store the part data and auto-recognize the component the next time it is being measured (see sidebar, page 24). For increased productivity, the HVR100-Flip can use robotic automation for parts loading and unloading.
Subjectivity and operator-to-operator variation in using an optical comparator with traditional overlays are replaced by the part CAD (DXF) file. This allows for easy updates, fast changes, and inspection repeatability.
Technological advances of walk-up metrology systems make them more functional and accessible to engineers, tool and die makers, machinists, and maintenance shop employees. When more disciplines of a company understand and use the technology, measurement processes are more efficient. Walk-up metrology’s capabilities also make it a discoverable technology, allowing a part to be reverse engineered by making measurements quickly and easily via a touch screen.
“Walk-Up Metrology solutions are versatile, offering a wide range of uses from engineering and development to reverse engineering, quality, and inspection,” Arenal says. “Companies can experience a rapid payback on this type of metrology system.”
The CK3M programmable multi-axis controller uses EtherCAT and encoder communication protocols to interface with various encoders and motors, providing high-precision synchronous control and increased machine performance.
With output speeds of 50µs/5 axes, the controller’s high-speed feedback enables precise path control in precision machining. Machine builders can incorporate their own advanced control with its support for ANSI C or an original programming language.
Boosting speed and horsepower has improved machining in recent years, but the industry is clearly moving away from more muscle and toward more brains. As with the International Manufacturing Technology Show (IMTS 2018) and Hannover Messe 2018, Taiwan’s major show last year – the Taiwan International Machine Tool Show (TMTS) held in November in Taichung, Taiwan – focused more on connectivity, controls, robotics, and Industry 4.0/Industrial Internet of Things (IIoT) integration. The following are highlights from major exhibitors at the show.
Despite predictions of steep declines in the automotive business, sales increased slightly last year, staying higher than 17 million units for the fourth consecutive year in 2018. And in commercial vehicles, Class 8 truck sales topped ambitious, double-digit sales growth goals with more strength expected in 2019.
It wasn’t supposed to be this good. Going into 2018, most predictions called for steep declines in auto sales, and in commercial trucks, last year’s gains were even higher than the strong growth that had been predicted.
Heading into 2019, most of the predictions appear similar to where they were a year ago, for many of the same reasons. Research groups and some automakers predict sales will dip slightly below the 17 million mark in 2019 but stay near that figure (General Motors is an outlier, predicting sales similar to 2018’s). The National Automobile Dealers Association (NADA) prediction of 16.8 million sales is near the midpoint of predictions and a figure that would still make 2019 one of the top five years in the industry’s history.
On the commercial side, growth should slow as most major manufacturers are operating at full capacity, with order growth only extending the backlog of unbuilt vehicles. Component suppliers improved delivery rates in the second half of the year, so there is some potential for the large vehicle original equipment manufacturers (OEMs) to boost production this year, but experts are calling for a 2019 plateau in build rates as producers work through their backlogs.
Most 2019 projections call for mild sales declines, but there’s a big difference between 2018’s erroneous pessimism and 2019’s forecasts – greater certainty. Going into 2018, major questions were facing the industry:
Would prices rise because of tariffs on imported steel and aluminum?
Would rising interest rates make monthly payments on new vehicles too expensive for consumers?
Would buyers continue opting for crossovers and SUVs in large enough numbers to offset declines in car sales?
A year later, we have answers – yes, no, and yes. Companies were able to pass higher metals costs to buyers by cutting cash-back incentives; interest rates rose several times, and the buying continued; cars continued their historic plunge in popularity, but bigger, new vehicles more than compensated.
For 2019, economists expect the Federal Reserve to keep rates steady or only raise them once or twice, eliminating that concern. Higher metals prices are pretty much baked into new vehicle pricing, so that concern has been addressed. And, several new SUVs and crossovers are heading to showrooms now or will be available by year’s end. GM officials are also predicting a strong 2019 due to a new line of pickups hitting showrooms, Toyota officials expressed excitement for the RAV4 SUV, and Subaru is increasing capacity for its SUVs.
Much of the automotive news in 2018 focused on the collapse in popularity for small cars – Ford’s announcement that it was scrapping most models by 2020, Fiat Chrysler’s (FCA’s) sales growth following its decision to eliminate car options in 2017, GM’s call to close five plants that produce cars or car components this year. As much as half of auto sales a decade ago, cars barely made up 30% of 2018’s numbers, and those figures could fall to lower than 20% this year following the GM and Ford nameplate eliminations.
FCA’s experience in 2018 could foreshadow great results for GM and Ford this year. The first automaker to dump most cars from its lineup, FCA was the fastest-growing major automaker last year with sales up 8.5%.
“This year's performance underscores the efforts we undertook to realign our production to give U.S. consumers more Jeep vehicles and Ram pickup trucks,” says Reid Bigland, head of U.S. Sales at FCA. “We see sales remaining solid in 2019 and we look forward to expanding our vehicle portfolio with the addition of the much-anticipated Jeep Gladiator (pickup).”
Patrick Manzi, NADA senior economist says low gasoline prices and better fuel economy for crossovers have been responsible for the shift to larger vehicles with “crossover utility vehicles nearly as fuel efficient as their sedan counterparts. And we’ve seen fuel economy increases across the board, not just on crossovers but also traditional SUVs and pickups. We also expect gasoline prices to remain relatively low in 2019, not as low as present but still low enough not to cause a panic and a consumer shift back to the car market.”
The NADA’s 16.8 million vehicles prediction is higher than the 16.7 million it predicted for 2018. Concerns about trade, the global economy, and signs that the U.S. economy may have peaked have NADA economists and others predicting declines again, though they are more optimistic than they were heading into 2018.
Dealers are especially concerned about decreasing affordability for new vehicles. The shift to larger, more expensive vehicles has been great for automotive profits, and consumers have been willing to pay higher prices for vehicles thanks to longer-term loans with low interest rates. OEMs have responded by lowering cash-back incentives, making vehicles more expensive. If interest rates continue to rise, monthly payments could shoot up, encouraging buyers to select smaller, less expensive options.
NADA Chairman Wes Lutz, president of Extreme Dodge-Chrysler-Jeep-Ram in Jackson, Michigan, says, “If incentives continue to go down and interest rates go up, it will put tremendous pressure on consumers with rising monthly payments. The level of interest rates moving forward will be a wildcard.”
Commercial truck 2019
First the bad news. Commercial truck orders slowed in the final months of the year. The good news – that was almost inevitable given the unprecedented order levels logged from late 2017 through the third quarter of 2018. And, given the massive backlogs for all of the major producers, the lower number of orders simply means the waiting lines for new vehicles won’t grow as quickly. If customers don’t order a single new truck in 2019, plants will still be rushing to catch up through the end of the year.
“For all of 2018, Class 8 orders totaled 490,100 units, far outstripping the previous annual order tally set in 2004 at 390,000 units,” says Kenny Vieth, president and senior analyst at ACT Research, a Columbus, Indiana, group that tracks the commercial market.
Executives at Paccar, Navistar, and Daimler trucks project higher sales for 2019, even if orders continue to slow. Navistar Chairman, President, and CEO Troy Clarke says companies are doing more than riding a wave of high sales. Commercial vehicle manufacturers are investing in new products, manufacturing efficiency, and technology.
“While we expect 2019 to be another strong year for Navistar and the industry, it's important to recognize that Navistar as an investment is much more than just a cycle play,” Clarke says. “As our ongoing improvements demonstrate, the company also has strong opportunities to benefit by recapturing market share, growing parts revenue, improving margins, generating free cash flow, and further de-risking the balance sheet.”
About medium-duty orders, Vieth comments, “After robust orders in November, Classes 5-7 orders moderated into the end of the year, falling to a six-month low of 21,500 units, and a considerable drop from the 25,200 unit-per-month average the medium-duty industry enjoyed throughout 2018.” He adds, “Seasonality is not a factor in December for medium-duty vehicles, but the month’s orders had the ignominy of being the first negative year-over-year comparison in 15 months, falling 4.6% compared to December 2017.”
In late 2018, Paccar CEO Ron Armstrong said increases in shipping, as customers order more goods for home delivery, coupled with fleets’ need to attract a shrinking pool of drivers by offering state-of-the-art new trucks is creating massive demand in Class 8 and medium-duty commercial vehicles.
“Kenworth and Peterbilt have received more than double the number of U.S. and Canada Class 8 orders in the first nine months of this year, compared to the same period last year,” Armstrong says.
Vieth warns that there are some signs that the commercial market may be slowing down a bit, saying economic indicators feature a few flashing yellow lights, though no red ones. The risk, he says, is a broad-based decline in the U.S. economy, not anything specific to trucking.
“Despite some caution creeping into the outlook, the heavy commercial vehicle market continues to benefit from a still-broad spectrum of supply and demand-side triggers,” Vieth adds.
Electric vehicle growth
Tesla Inc. finally hit volume production in 2018 following years of misses, and its rapid growth from 2018 should continue into 2019. The California-based electric car maker had intended to reach a 250,000-unit annual build rate on its Model 3 vehicle by the end of 2017 but missed that target badly. Tesla sold about 146,000 Model 3s in 2018, and it reached a 250,000-vehicles-per-year build rate in the final quarter.
“We started the year with a delivery run rate of about 120,000 vehicles per year and ended it at more than 350,000 vehicles per year – an increase of almost 3x,” Tesla officials say. “We’re starting to make a tangible impact on accelerating the world to sustainable energy.”
The company is still far from its goal of making affordable electric cars for average drivers – the Model 3s produced last year and for the foreseeable future were $50,000 units, not the $35,000 ones the company hopes to eventually make. However, it delivered nearly 250,000 units between its Model S, Model X, and Model 3, more than 5x the electric vehicle output of the combined GM Chevy Bolt EV (electric car) and Volt (plug-in hybrid), Nissan Leaf, and BMW i3 and i8 electrics. That puts electrics at about 1.7% of the U.S. market, up from 1.1% in 2017.
Traditional automakers had mixed electric results last year. Honda’s Clarity plug-in hybrid (PHEV) beat Chevrolet’s Volt to become the country’s favorite PHEV. Chevy has stopped producing the Volt. And while the Chevy Bolt all-electric car posted a 23% decline for 2018, GM officials say they’ve boosted production and expect much better numbers in 2019.
Tesla’s production successes, coupled with more aggressive electric plans from traditional automakers, could push electrics higher than 500,000 units in 2019, putting those vehicles on pace to hit about 3% market share.
Any growth Tesla experiences this year will be without the benefit of a $7,500 tax credit to encourage electric vehicle purchases. Tesla exceeded electric vehicle volumes for the credit in 2018, so its vehicle’s buyers can only receive a $3,750 credit this year, falling to nothing in 2020 (unless Congress passes new tax rules). GM’s Chevy Bolt is also slated to lose portions of its tax credits. Tesla responded by cutting vehicles prices by $2,000, making up much of the difference. But price hasn’t been much of an issue for Tesla, which sells the vast majority of its vehicles to luxury buyers willing to pay premium prices.
The automotive industry is undergoing its most important transition since the introduction of assembly robotics and automated work cells. The interconnected world of personal devices and Internet of Things (IoT) is already present in vehicle design. Greater factory automation and learning systems are just a corner or two away. For the automotive design, manufacturing, and systems engineer, the quality of the digital master model that will transform and command these interdisciplinary functions is critical.
Data must be as unambiguous as a paper 2D drawing once was for machining and as chock-full of product information as the file cabinet in a director’s office – only now it must be instantly accessible globally to machines awaiting instruction or a computational fluids analyst studying an injection, exhaust, or brake system.
Digital design in automotive
The automotive industry still rides on uneven pavement in the digital world. Its centerpiece for containing product information, the computer-aided design (CAD) system, derives largely from several key vendors with proprietary math kernels defining shapes and surfaces. Third-party contributors of specialized software add to the different recipes, which do not communicate uniformly and in agreement, despite advances in STandard for the Exchange of Product model data (STEP) and other neutral file formats. Small human errors or digital discrepancies in edges, faces, tolerances, or draft angles often remain, interfering with everything from a finite element analysis (FEA) to a press operation.
Why does digital quality matter in an industry that has succeeded by navigating its own legacy tools and practices? Global competition increases annually, making no geography or brand safe from breakthroughs in performance, cost, and appeal. Trends sweep in quickly, such as the move to SUVs from cars. Whole platforms, assemblies, and exteriors may need to change instantly to accommodate new markets or external requirements. More accurate, reliable digital systems can quickly take manufacturers down new roads.
Design intent, virtual testing, and validation must travel via the CAD model to downstream production and inspection stations and back again to design for continuous improvement. The one central element that all these systems must share is accuracy and readability.
Twists in the road
Unlike aerospace, which at this moment leads automotive in establishing digital uniformity, vehicle makers have significantly tighter financial margins, shorter product life cycles, shorter development cycles, and fewer internal and external resources (such as NASA or DARPA) to explore model-based definition (MBD) and the model-based enterprise (MBE). Aerospace leaders have mandated MBD for at least their Tier 1 suppliers. In automotive, Tier 1s seem to be responsible for bringing into agreement data from their sub-tier suppliers and the original equipment manufacturers (OEMs). Being in the middle of the data hub often forces the Tier 1 group to lead data integration by example, enforcing best practices by default.
Since all OEMs have their own set of modeling requirements as deliverables from suppliers, Tier 1s must replicate each OEM CAD environment to achieve acceptable delivery. These requirements often include different CAD formats, software versions, and flavors that are specific to each OEM as well as individualized rules about geometry quality, metadata, usage of layers for product manufacturing information (PMI), and delivery mechanisms. Tier 1s manage more than 30 CAD environments – and those have different versions and practices within vendors.
When Tier 1s reuse core knowledge that goes into their products to create custom variations, they must manage different OEM environments and update their ongoing changes into each system throughout the engineering journey, without losing fidelity. At the same time, they must adapt and pass different sets of quality criteria.
Manufacturers don’t want engineers spending time to manually solve these oversight functions. Engineers typically want to focus on the design, test, and production, not coding nuances within CAD/computer-aded manufacturing (CAM)/computer-aded engineering (CAE) that manifest problems in hard-to-determine areas. Yet these code-related issues can block precision machining and cause rework and delays in every discipline.
The solution is in independent quality and translation software systems – driven by native application programming interfaces (APIs) unique to each CAD program – that bring supplier geometry and the digital package of annotations and manufacturing instructions into a target master model of the OEM. Such automated back-end processing can overcome costly manual repairs, interruptions, and uncertainty.
Suppliers want to solve model discrepancies through a seamless conversion between these 30-plus environments, including unifying underlying data points sent to neutral formats such as STEP and IGES. Many manufacturing and engineering programs are designed to consume these standards of exchange, such as CNC toolpath generation and Parasolid translation for analysis software. The key is a conversion platform that can be easily executed and produce a reliable output so that the end user can immediately perform intended work.
Another goal is doing a preliminary product data quality (PDQ) check before information has been submitted to a supplier, having the toolset to customize PDQ checks to accommodate multiple profiles, and the capability to apply checks to CAD output or a neutral format.
Ideally, a Tier 1 can standardize on a single platform, optimize all products in a primary CAD environment, and simply convert to any necessary target system, conducting a PDQ check before the data is submitted to a customer. Quality problems can be pre-detected and addressed internally in a more automated process, and the model becomes ready for delivery with confidence that it will pass. This approach keeps the OEM from having to reject models, unravel the issues of an unfamiliar system, and re-iterate the process throughout days and sometimes weeks.
Automotive components and systems can generate more than 100 revisions, and required migration steps to new CAD software systems create additional pain points. MBD can support producing vehicles more quickly and less expensively than before. Factory automation must be supported by accurate, all-digital platforms that create clean, quick pathways from CAD to machine systems to inspection programs, and back again to the original CAD model for confirmation of end quality. Advanced healing, validation, translation, and PDQ technology can smooth this vision of automated digital design and production.