Managing Automation - May 2008 - (Page 9)

each order, a process that could take 45 minutes. “Our whole goal in the U.S. was to be digitally skilled, but it’s a problem when, because of the software, a highly skilled person can be more efficient than a machine,” Shaffer said. At the same time, Otabo suffered because shoe materials suppliers and others that were needed to support a high-volume manufacturing operation are, increasingly, simply no longer doing business in the United States. People who knew how to operate and maintain Otabo’s robots were difficult to find, and leather suppliers and tanneries were going out of business. “We ended up having to get materials from Europe or China at greater cost than everybody else,” Shaffer said. Also, Otabo’s intense focus on perfecting its digitally driven manufacturing process caused the company to overlook other aspects of its business, such as marketing, the CEO said. The company has lined up only 30 retail partners to date, a far cry from the 150 it had hoped to have by the end of 2005. Otabo’s move to China will allow Shaffer to focus more on building Otabo’s retail network while continuing to support the company’s masscustomization business model. Although Otabo’s production partners in China will do the sewing by hand, improvements in the software that the company uses to digitally model the shoes will reduce production lead times. Once production in China ramps up — as early as August — Otabo’s goal is to deliver on custom orders within two weeks. Order turnaround time from the U.S. plant had been four to five weeks. Meanwhile, the timing of Otabo’s move to China seems to be favoring the company. With increasing pressure being applied to Chinese shoe manufacturers from lower-cost countries, such as Vietnam, many surviving shoe manufacturers in Guangzhou realize they need to move away from competing simply on the basis of lower labor costs, Shaffer said. For that reason, he said, many are interested in teaming up with him in support of his mass-customization business model. “It’s become apparent right off the bat that we can do this in China,” said Shaffer, who has extensive experience there having helped set up Nike’s first Chinese plants in the early 1980s and later running his own China-based contract manufacturing company, Sabry Jen Co. Ltd. Still, Shaffer was wistful about turning away from his dream of re-establishing a U.S.-based shoe manufacturing industry. “You can’t say we didn’t try,” he said. “We put a really good effort into it. We just could not make it happen.” IBM PARTNERS WITH UNIVERSITIES FOR CLOUD COMPUTING he clouds are gathering, and IBM couldn’t be happier. In conjunction with the Georgia Institute of Technology and Ohio State University, Big Blue recently announced that it will create the Critical Enterprise Cloud Computing Services facility, a “prototype computing cloud that links data centers from the two institutions,” according to an IBM statement. The recent profusion of the term “cloud computing” has left some people wondering what’s behind the marketing vapor. In the context of IBM’s work, cloud computing is a virtualized data center with automated management of functions that once required hands-on attention from IT staff. Through its joint efforts with researchers and students at the two schools, IBM is pursuing a twofold goal: using the university brain trust to identify and begin developing computing technology that it can eventually commercialize, and seeding the next generation of IT engineers with the skills needed to manipulate technology that baffles ordinary computer users. For those new to cloud computing, Frank Gillett of Forrester Research suggests a review of data centers and virtualization. Before the emergence of virtualization — and still today — IT departments often loaded one application on one server, even if that meant utilizing just 40% of the server’s capacity, because they wanted to keep the data isolated and guarantee reliable application performance. Virtual servers maintain that isolation while drastically increasing utilization rates. “The whole virtualization thing was kicked off by the idea of subdividing a computer — having one computer pretend to be many in order to put more things on a computer that otherwise was not very busy,” Gillett said. IBM and other providers working in the cloud apply the virtualization concept across vast data centers. “When we talk about cloud computing, what we’re actually talking about is scaling that up to very large numbers of machines supporting very large numbers of transactions,” said Matt Ellis, IBM’s vice president of autonomic computing. In the broader business and consumer worlds, cloud computing is the engine that drives many popular Web services, including Google searches and the software-as-aservice applications that vendors, from SAP to Scan M Back M A M AY 2 0 0 7 inMA T anufacturing executives were determined to finally deal with the proliferation of systems and applications, ad hoc procedures, and insufficient integration that stood in the way of operating efficiently on a global scale and meeting growing regulatory requirements. What was needed was a unified architecture based on open standards, as well as process changes and performance metrics to measure progress. This was a tall order, but big manufacturers were moving in the direction of the “one enterprise.” M A M AY 2 0 0 3 E nterprise software vendors were touting a new generation of business process software called composite applications as the answer to the decades-old problem of software application integration. To use these applications, manufacturers would have to re-engineer their thinking. They would have to ignore individual application boundaries and be willing to dismantle the walls between their internal divisions and functions. Contemplating that shift raised questions about whether the software would really enable manufacturers to compute more seamlessly. M A M AY 1 9 9 8 anufacturing companies were lining up on the dock, eager to take the plunge into cyberspace where they saw the Web’s potential to tighten their supply chains by linking their suppliers to inventory, order, and production systems. Pioneering companies reported shorter product-to-market cycles, lower cost, greater buying power, and quicker response to customers. Even so, the Internet didn’t eliminate the integration challenges in linking disparate ERP, supply chain management, and planning and logistics management applications. M M A M AY 1 9 9 3 utomatic identification, including data collection technology, was a fastgrowing area as manufacturers sought out technology that could help them automate data acquisition and then process and analyze the data they had collected. The PC’s advancing ubiquity was helping to propel data acquisition into the factory setting, as were bar-code readers, RFID, optical character recognition, machine vision, and magnetic stripe, and other technologies. A 9 May 2008

Table of Contents Feed for the Digital Edition of Managing Automation - May 2008

Managing Automation - May 2008 Contents Take 1 Award-Winning Shoe-Maker Otabo Alters Course, Shifts Production to China IBM Partners with Universities for Cloud Computing Getting Noise in Production Under Control Incuity Embarks on a Vertical Market Strategy Foundation Intensifies OPC Standard Testing Mailbox Notes PM Roundtable Cover Story: The Business of Going Green Special Report: Night and Day Delivering on Promises Finding the Right Fit for Wireless Driving RFID Product Scan Advertiser Index Next

Managing Automation - May 2008

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