Ford Motor Co.

    Indianapolis, IN, USA
      Customer Objectives:
      • Inspect valve bridges to ensure proper positioning and alignment
      • Confirm correct engine assembly
      Key Results:
      • Automated inspection, expediting assembly verification and reducing labor costs
      • Maintained consistent product quality
      • Successfully completed inspections while maneuvering around variable parts and obscurations
      Cognex Solution:

      Robot-guided inspection system ensures correct engine assembly

      International Truck and Engine Corporation has recently implemented an innovative robot-guided inspection system at its manufacturing plant in Indianapolis, Indiana to verify the proper placement of valve bridges during assembly.

      The diesel engines, which are produced for large Ford pickup trucks, feature 16- valve bridges, which sit on top of the engine’s valve stem. During head assembly, the valve bridges are placed on top of the valve spring and a rocker arm is placed on top of the bridges. This whole assembly is then placed onto the engine. Prior to being installed on the engine, the valve bridges are only loosely held in place by the rocker arm. It is necessary to inspect each one to ensure they are positioned accurately and that none of the components have become misaligned.

      While the company has always achieved accurate, 100% inspection of its engine components, the inspections had been carried out manually. An operator would look down into the engine assembly, check each individual valve bridge for placement, and mark each one with a paint pen to indicate that it had been inspected. The process was slow and costly from a labor standpoint. The time had come to automate.

      Having successfully implemented robots in other areas of production, International felt that a robot might be useful in this case, and called on CIM SYSTEMS INC., a Noblesville, Indiana-based systems integration firm that specializes in robotic automation. According to Tony Hillers, a CIM SYSTEMS engineer assigned to the project, a robot-guided inspection station was the perfect solution.

      “We all felt that robot-guided vision would be the most flexible solution in terms of being able to automatically inspect the parts inside the engine,” he explains. “They could have set up a little finger probe that actually touched the part to do the verification, but the parts are difficult to approach consistently. With vision, we’d be able to avoid any problems associated with a contact approach.”

      One of initial ideas for a vision system, Hillers adds, was to have 16 separate vision cameras mounted above the inspection point, allowing for one camera per part. The problem with this approach, however, was that the engine assembly is very full with components, and wires and other parts often occlude the valve bridges. “We needed a way to allow a single-vision camera to move in and around the engine assembly in order to actually get a look at the parts even when other things are obscuring them. Positioning the camera with a robot allowed us to implement logic that enabled the robot arm to try to see the valve bridge from multiple angles.” Hillers also notes that a 16-camera vision system would have been an expensive option, and would require a great deal of maintenance.

      The main components selected for the project included a single Cognex In-Sight® vision system and a six-axis ABB IRB 140 robot. The In-Sight series has high-performance machine vision systems that consist of a industrial-hardened, DSP-based vision processing unit, high-speed digital camera that easily mounts to the robot arm, onboard light control, built-in discrete I/O, and a pre-installed vision library of greyscale vision software tools. The In-Sight series also provides a standard VGA output for real-time display, built-in Ethernet communications, and an onboard serial port which is used to link to the ABB robot controller.

      To set up the 16-point inspection routine, Hillers used the In-Sight vision sensor’s spreadsheet interface. With the look and feel of a traditional spreadsheet, the In-Sight vision spreadsheet enabled him to quickly select vision tools and parameters from drop-down menus, and configure a customized operator interface to make day-to-day operation of the system easy for line operators, technicians, and maintenance staff at International. “It was easy to explain how it works to shop floor personnel,“ says Hillers, “and people with no programming experience were able to make changes to the program in one day. If you can understand Microsoft Excel even a little bit, then you can pick up on it and go with it.”

      Engine blocks come into the cell on a floor-mounted conveyor, each sitting in its own nested pallet. Once an engine is present, the IRB 140 hovers over the engine block, positioning itself this way and that so that the vision camera can get a good view of the parts. If the camera can’t see a part, the robot repositions itself at various angles until the part becomes visible. To increase visibility, the parts are illuminated with a combination of a ring light, which is attached to the tooling on the end of the robot arm, and side-mounted fluorescent lighting.

      Once a valve bridge is in view, the robot controller sends a signal to the vision camera to capture an image of the part. The image is then sent to the In-Sight vision processing unit, which is mounted in the robot controller enclosure, and processed with In-Sight’s PatFind® tool, a geometric pattern-matching software tool that verifies the proper position of the part despite any occlusions or variations in part appearance that may exist.

      According to Scott Hauger, a CIM SYSTEMS applications engineer who worked on the project, pattern-matching performance factored heavily into the decision to go with the Cognex system. “The valve bridges have a unique shape, and with so many components in the way it’s critical that the vision system is able to pick out the right features,” says Hauger. “The PatFind tool does just that.”

      PatFind analyzes images using geometric information in place of pixel grid-based correlation.  For example, it interprets a square as four line segments and a football as two arcs. By analyzing the geometric information from a part’s features and spatial relationships, the PatFind tool is able to precisely and repeatably determine the precise position of each valve bridge in the engine regardless of how it appears.

      As each of the 16 valve bridges is inspected, operators can view a live image display of the parts on a nearby color monitor. The display lists the different valve bridges by cylinder number, and provides pass/fail information for each inspection. If all 16 parts pass inspection, the engine proceeds down the production line to a testing area.  If a failure is reported, the robot controller passes the information to a line control system to be written to an RF Identification tag. At that point, the engine goes into a repair loop where an operator manually inspects the parts in question. It is then re-routed through the cell and inspected by the In-Sight system again.

      Since the robot-guided inspection system was installed, it has been running non-stop for two shifts per day without any problems. According to Hillers, product quality has remained consistently high, and International is pleased to add this project to its long list of successful automation stories.

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