Mind the gap! Small data variations may suggest big problems

3 min read

Alex Cook of Chemigraphic explains why even small variations in production data need to be taken seriously

Quality measurement plays a pivotal role in helping drive stability, prosperity and growth - and that's good for everybody, especially in these uncertain times. Within the details of quality data are small differences - gaps - between predicted and actual results, and a thorough examination of these gaps, even relatively small ones, can point to wider issues of commercial management. Minding these 'gaps' goes beyond just collecting quality metrics and conformance data, it's about getting to the root cause in order to be operationally-efficient and ultimately sustainable, with all the benefits this brings to customers.

Even small data variations can have great significance

We'll look at a few areas where a rigorous 'mind the gap' ethos within commercial management can deliver clear customer advantages.

Scrappy data leads to higher costs

Scrap is the commonly used term for what's rejected as "non-compliant" after a production job. The usual issues are damaged or faulty items, which can be blatant, but can also include less tangible issues as borderline tolerance issues, temperature or time-dependent failures, failures under one set of circumstances but not another identical situation, and subjective defects, especially cosmetic imperfections. Companies may absorb scrap as an inevitable cost of manufacturing but failing to at least track and investigate the causes of scrap can be a lost opportunity to identify a number of issues: inefficient manufacturing processes, supplier problems, inappropriate or poorly applied acceptability criteria, tooling issues, manual and handling issues or even poor documentation.

We make sure that even relatively small value materials are quarantined and go to a Material Review Board (MRB) that consists of sales, quality, purchasing and production, where a joint decision is made on disposition. The MRB asks questions like:

  • What's the root cause of this material being segregated and quarantined?
  • Are defects physically repairable? Will the result be fully compliant? Will the repair be acceptable to customer? If not, will the customer concede in this instance. Should we instigate a new repair process?
  • Is there an underlying defect in supplied materials and can this be compensated by the supplier?
  • Is a material truly non-conforming or just sub-optimal? Is the acceptability criteria properly defined and applied?
  • What is the repair cost vs replacement cost vs item value? Are there other strategic reasons for extra efforts for recovery in this instance, e.g. to complete a consignment; no time to source alternatives; a one off build is inefficient, or other reasons.
  • Is this incidence part of a trend? i.e. the individual part value may be insignificant, but the ongoing accumulated cost could be substantial.
  • Is this incidence an indicator of a wider or more systemic problem? Will the benefits of a corrective action improve capability in other areas?

This MRB process also helps to ensure that standards are correctly interpreted.

Scrapping not only has a direct effect on materials used in production and costs money but there's time and labour spent dealing with the disposition. Monitoring the scrap data provides opportunities to build leaner manufacturing processes by looking at:

  • Who is handling the materials and how frequently?
  • What are the costs of scrapped materials?
  • Can any parts be salvaged for reuse of return?

Longer job times can actually lead to better business

Every production job has a job time. These may vary enormously - and even on repeat builds job time can vary depending on which operators have been assigned and the batch size. Typically, we put a traffic light system in place to monitor the data. From a commercial management perspective, it's important to focus on growth and stability and ask questions around the red and amber lights:

  • Why did that job make nothing?
  • Is that a continual loss making job?
  • Was there an excessive amount of scrap on the job?
  • Did we over-run time?
  • Where did that cost occur?

Growth and stability improvements are typically made not from simply replicating sales in the best performing customers but looking at the bottom performing jobs and addressing those issues. By collecting quality data over a long time, it's possible to determine whether there's exceptional circumstances or a persistent problem.

The return of the return

Returns under warranty happen for lots of reasons. Where a product doesn't function in the intended manner due to a fault then it is clear the responsibility lies with the manufacturer and it is their liability to fix the problem. However, a product may ping-pong back and forth between manufacturer and supplier before somebody intervenes to halt the process. By then there may be limited options, having been inspected by both parties without anybody accepting liability. In these instances it remains very important to maintain accurate detailed data.  There might be an underlying quality defect - a board might be delaminating after the components are mounted, for instance. This would be an issue of the materials supplied and in these instances it might be appropriate to address issues of compensation with suppliers.

The age of returns is critical too. Within the complex and fast-paced transactions of a modern manufacturing environment, materials can be put aside for a variety of reasons. Over time the pile can accumulate. When someone eventually addresses this pile of returns, the original reasons for the segregations may be lost and it can be tempting to simply return the goods to the supplier.

Detailed quality data generates lots of opportunities to improve a process. Being mindful of the small gaps in quality data makes a big difference in the long run.

Alex Cook is NPI and Sales Systems Manager at Chemigraphic, an electronic products manufacturer working with OEMS across medical, industrial, rail, marine and power industries amongst others.