Bin picking has a clear vision

A successful vision-guided robot project required the specialized contribution of several talented technology application providers in order to meet objectives for more flexible, reusable automation.

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 By Adil Shafi, President, Shafi Inc.

There typically are several motivations to use vision and robots for manufacturing. Labor savings, clearly, is one of them. While labor costs tend to stay the same or rise, they also recur every year. The cost of automation is declining and primarily is a one-time purchase. Because American manufacturing often is at a distinct disadvantage against overseas labor costs, typical ROI calculations for these labor-saving solutions are less than one year, while the length of a parts manufacturing program is typically five years.

Throughput is another issue. Manual operations often are upstream in a manufacturing line, so a manual operation that loads parts at the upstream station often controls the throughput of the line. This is amplified when the parts are large, sharp, or heavy. It may be that the line itself contains automation such as welding robots, but efficiency is controlled by the rate of entry of product into the line. Automating these throughput-controlling operation benefits the cost structure of the overall manufacturing operation. Manual operations also generate costly injuries, most of which could be avoided.

Vision Guided Robotic (VGR) solutions can solve these problems and provide more flexibility, allowing product changes to be handled with the same means for conveyance, e.g., racks, boxes, trays, conveyors, etc. When product changes are made, shutdown and a retooling aren’t required to manage new product geometries.

VGR Investigation
About a year ago, Dan Bickersteth, corporate manager for cycle time improvement and automation at Detroit-based American Axle and Manufacturing (AAM), took an assignment to champion his company's automation efforts. "We surveyed all our facilities and rank-ordered the automation opportunities," says Bickersteth. "Our objective was to establish a hit list that we could pursue that would maximize our capital resources allocated to automation."

During the same period, looking toward future needs, AAM selected robot partners and system integration partners. With the list in hand and the technical partners in place, Bickersteth set out to tackle the 2004 projects.

A machine vision initiative arose from of a need to reduce low-value-added work assignments such as axle shaft and pinion bin picking, pick/place operations, etc. "Our existing dunnage [parts container] does not provide any consistent part positioning," says Bickersteth. "However, I recognized that there are patterns to the unit loads."

In automated bin picking applications, products typically are randomly piled in the box or bin. (See sidebar below this story) This creates a challenge to find the parts, determine their orientation in 3-D space, and grasp them in spite of their varied resting positions.

Traditionally, these applications have offered the most promise for cost savings, but from a technical solution standpoint, have been the most elusive. However, with recent advances in machine vision technology, robotic end-effectors and 3-D calculation software, these solutions now are becoming more feasible.

Traditionally, both the axle shaft and the pinion picking operations were done manually. In the case of the axle shaft cell, AAM factory personnel handled an extremely large amount of material in a single shift. "We pursued this automation initiative not only for cost reduction, but also to eliminate an ergonomically demanding work assignment," says Bickersteth. "Automation also provides consistency. If the cycle time requirements are suitable for automation, we would see good results."

One of AAM's suppliers, Nachi Robotic Systems along with vision software solution developer Shafi Inc. suggested a VGR solution that might automate the manual bin-picking operation. Shafi specializes in turnkey solutions for vertical applications that involve robots and machine vision.

"Nachi is the first robot supplier to be involved with axle shaft and pinion picking operation at AAM," says Frank Seitz, of Nachi. "On this particular project, we supplied a six-axis robot that features a large working envelope and backward reach, a versatile feature that allows for quicker material handling."

The SH series robot selected is capable of handling payloads of 133-200 kg. "Our AX controller," adds Seitz, "is a high-performance, multitasking, PC-based controller. Programming is fast and flexible with additional options available through the teach pendant. It also features an internal manual/diagnostic function so that maintenance can be done remotely."

Build on What You Know
Automating the axle shaft and pinion bin picking operation is not AAM's first venture into applying machine vision. "We used machine vision in other areas, but with mixed results," says Bickersteth. "This was to be our first attempt with robot guidance, so I did my research. Shafi received very good feedback from its customers."

The only other outfit Bickersteth found that was pursuing these types of solutions was Braintech, a Vancouver, B.C.-based company "However, they are aligned with ABB, and it was our desire, in this case, to work with Fanuc, Motoman, and Nachi. The Shafi system's flexibility was proven when the axle shaft project was successfully integrated with both a Nachi SH133 robot and a Motoman HP165."

Shafi specified vision hardware and invited Cognex into the project. "The Shafi contribution to the project provides the "glue" that keeps vision and robots easy to use by providing enabling software that tightly integrates robots and vision," says Herb Wagner, Cognex's senior regional manager.

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