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As today's market place becomes more global, Original Equipment Manufacturers (OEM) are faced with increased competition, shorter product life cycles, and higher customer expectations all resulting in strong financial pressures. Organizations are challenged to lower costs, improve quality, and bring better products to market faster. Realizing they cannot accomplish this entirely within their own organization, OEMs are outsourcing not just manufacturing but product development activities. Instead of designing products internally and then contracting for manufacture, companies are collaborating on product design.
This new collaborative engineering supply chain has raised the importance of engineering product data and introduced complex requirements for product data exchange. With frequent design changes, it is imperative that this valuable engineering product data be exchanged quickly and efficiently while protecting corporate assets.
Many companies are struggling to achieve this seamless and effective data interoperability. The National Institute of Standards and Technology (NIST) reports that the North American automotive industry alone wastes more than $1 billion each year because of the inability to freely share and reuse product data. It is safe to say that this represents only a tip of the global product data exchange iceberg. This paper will examine some of the issues and ways that companies are solving them.
Engineering Supply Chain Challenges
Lower costs, better quality, and faster time to market are all compelling reasons for manufacturing companies to scrutinize and reform their engineering supply chain. With a downturn in the economy, it seems every company has mandated reductions in costs while raising quality and automating processes. In short, do more with less. Engineering and manufacturing managers are told to become "model centric" to "reuse product data" to "integrate engineering processes" and to "collaborate with partners and suppliers". With such abroad task at hand, many struggle with where to begin.
Certainly the top challenge in collaborating between engineering organizations is the multitude of CAD (Computer-Aided Design), CAM (Computer-Aided Manufacturing), CAE (Computer-Aided Engineering) and other PLM (Product Lifecycle Management) systems in use ? each with its own proprietary and incompatible data formats. With hundreds or thousands of partners, just keeping track of the requirements for each partner and ensuring the right data is delivered to them is difficult. Frequent mistakes result in repeated efforts.
Getting data to a partner in a usable form can also be problematic. Data must frequently be translated to the compatible proprietary formats of the collaborative partner. Whether direct translators or neutral formats such as IGES and STEP are utilized, partners often report they spend substantial time and effort making CAD models usable. Anytime a model is changed, errors and quality issues can be introduced. Compounding the problem even more is the reluctance of suppliers to share these problems with their customers. Instead they pass this non-value added rework effort back to their customers as increased cost with longer delivery times.
Yet another substantial challenge is the actual data exchange process. When data must be translated to another format, it is often a manual process that consumes valuable engineering labor that could be better utilized to add product value.
Transmitting the data to the end recipient is another manual process that further consumes valuable personnel resources.
And what about securing the data and managing its release as part of the product development cycle? It is important that engineering intellectual property be safeguarded and that the right data be provided to partners.
Solutions
In order to better leverage the capabilities of partners, suppliers, and customers, an efficient and reliable method is required to manage product data sharing throughout the supply chain. ITI TranscenData has worked extensively with industry leaders including Xerox, Kodak, Cummins Engine, Johnson Controls, Samsung, Seagate and others in understanding key issues and developing solutions that fit into their environments. The following are some of the key elements to consider when developing an effective solution.
Automation to Eliminate Manual, Time Consuming, Error-Prone Processes
To ensure efficiency, the solution must automate time-consuming manual translation and transmission processes. In addition to expediting the process, this eliminates many error-prone manual steps.
Expertise to Ensure High Reliability
Automation alone is not enough ? especially when translation is involved. It must be automation of "Best Practices" which result in accurate and usable data once the translation is complete.
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