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With the EU RoHS deadline well behind us, most companies have implemented some kind of environmental compliance management program by now. The question nowadays is not how to be environmentally compliant but how to do so in the most efficient way. Without a good set of tools, compliance management can quickly become a big headache for all parties involved. As the understanding of environmental regulations and procedures mature, we are also beginning to catch a glimpse of best practices that can expedite the compliance management process.
Of the steps leading up to compliance declaration, data collection has stood out as a major bottleneck for most companies in the compliance management process. Most tend to underestimate the amount of effort that is required to collect the necessary component data for compliance analysis and validation. The lack of preparation before undertaking data collection further complicates the problem and extends the time lag in the cycle. There are, however, critical steps that can alleviate data collection grief.
Step 1: BOM scrubbing/parts cleansing
Starting a compliance management program with a clean slate is something that makes sense to everyone, and yet, is often overlooked. Dirty data from ERP/PLM systems can lead to unnecessary overhead going into compliance management. Problems such as duplicate part numbers and inconsistent manufacturer naming will increase both time and resource costs during the data collection stage. In some cases, these issues can also lead to error.
Investing internal resources to clean up parts data is one way of resolving the issue. However, this option might not be very realistic under certain circumstances. Small and medium-sized companies often will not have ready resources to spare on this time-intensive task. Even larger manufacturers will have problems with insufficient resources where a quick data turnaround is expected. In these types of situations, companies can consider external data service providers. With focused expertise, these services are usually able to clean up dirty data in a comparatively shorter amount of time as it would take internal resources.
Step 2: collect data on commodity parts
After the parts data is cleaned and ready to go, data collection can be initialized. While some may immediately rush to suppliers or distributors with data collection requests, it is important to realize that a good portion of the data you're seeking might already be available online. More and more component manufacturers are beginning to publish not only RoHS status information but also full material composition disclosure through company web sites. Heading to these sources for compliance information on commodity parts will give your data collection process a jump start.
In practice, many issues arise, most stemming out of the question of whom to assign this task to. In some cases, the data collection task is given to the procurement team since they're most familiar with current suppliers or distributors. Unfortunately, procurement, more often than not, lacks the knowledge or expertise to correctly identify the information they're seeking. For example, procurement will usually use manufacturers' part numbers to look for part material composition data. However, many parts only have their material composition information listed based on package type, without part number associations. Circumstances like these can significantly stall the data collection process. At times, engineering resources are employed to complete the task of data collection. Though domain knowledge is no longer a concern, this choice carries an obvious cost to product development.
Utilizing RoHS database solutions may resolve these issues while providing additional advantages. Two key benefits of database solutions are that they provide fast results and relieve the user of maintenance concerns. These systems not only provide the user with instant download of material composition data but will also automatically update when the compliance status changes, parts become obsolete, etc. The decision between choosing to commit internal resources and using a database solution should be based on a thorough cost analysis.
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