Siddall & Hilton Products in search of efficiency gains

Complex business challenges

Siddall and Hilton Products doesn’t just manufacture a diverse range of products, it does so in a wide variety of sizes and order quantities. 60-70% of all orders are Make to Stock (MTS) with the remainder being bespoke. Depending on what product is on which of the company’s state-of-the-art machines, production rates can be as high as 15 seconds per panel with each order potentially running for hours if not days. And as Operations Director Phil Goy explains, the majority of orders tend to be a “complete mix of everything.” A brief overview of the actual manufacturing process begins to illustrate the business challenges that the company faces on a daily basis as well as at a strategic level.

• The raw material stock arrives on 1 tonne coils of wire which are then loaded onto decoilers that feed through various straighteners into the main section of the machine.
• Depending on the size of the panel, there may be up to 61 decoilers which need to be loaded, with coils up to 1 tonne in weight.

It is no wonder that Goy remarks, “Set-up and changeover times are areas that clearly need to be monitored and optimised!”

The company was aware that setup times were often taking too long but not sure which elements of the set ups were taking the time.

Similarly, unscheduled breakdowns would often occur and it wasn’t clear why and there was no means of knowing how long a machine may be idle as a result.

The Operations Management work for one shift a day, the machines for three Shifts, and monitoring of performance was inadequate. Goy again, “Any errors or problems were manually written on a piece of A4 paper which was then entered into a spreadsheet at the end of the day which eventually, hopefully somebody might analyse. In short, the process was time consuming, wasteful of resource, and led to information that was questionable, analysis that was sporadic and nil action.”

With accurate, real-time data was essential to the company’s ongoing efficiency plans, Goy was tasked with sourcing an appropriate solution. A Seiki account manager came on-site and ran a simulation based on live data.

Understanding the importance of getting buy-in from all relevant people in the company, Goy assembled a team comprising the Managing Director, the Production Planner, relevant technicians and operatives, the company IT specialist and Quality Control personnel.

Improved visibility

“This was an essential step in demonstrating the importance of improving the uptime of our resources through improved visibility of machine activity and individual job performance” explains Goy. “I was able to show everyone by fast forwarding through 20 hours of video footage just how many stoppages we were having and how little we knew about each one.  This was contrasted with the way the Seiki system monitored every stoppage, the reason for every stoppage, and the ability to then analyse the reasons. “It was clear that Seiki theoretically could do what we needed – all we needed to do was build a capital case to get the go-ahead.” 

Goy already knew that the company had lost 130 productive shifts on just one machine in the previous year due to changeovers with each shift costing approximately £800. Incremental profit lost due to changeovers approximates £18k. A projected 20% efficiency saving from the Seiki System would therefore be £3.6k p.a. When the same analysis was applied to reductions in scrap and rework it became clear that the company was looking at a Return on Investment (ROI) in under 2 years. And this was only for one machine with each of the other machines having an even quicker ROI due to the expertise that would be acquired in setting up the first machine.

Results

Now whenever a machine is stopped, the data is instantly recorded. If stopped by an operator, the reason for stoppage has to be manually entered along with any subsequent actions. Not only is the duration of each subsequent action logged, but the time between an information request and that information being supplied is also stored.

This became especially useful when the company trialled a move to a 24×7 shift basis. Goy reflects on the impact this made. “With each passing day we had a growing insight into machine activity and inactivity which we could analyse by shift, operator, and stoppage code. It wasn’t long before we had enough visual information to drill down into to know where the biggest areas of efficiency gain could be most quickly achieved.”

On the first live machine this led to an innovative reworking of the 61 decoilers and workflow which has reduced the most common changeover time from 4.5 shifts to 1.5 shifts. This combined with other efficiency gains that are directly attributable to the Seiki System has led to an effective doubling of machine uptime.

And when the other systems came online, the company very quickly began to accurately see how each machine had different areas of potential improvement. Goy again, “We could clearly see what we already knew, that 1 machine works better with multiple changeovers with medium duration runs whereas another has much longer setup times but much fewer stoppages. The Seiki output allows us to visualise and quantify improvement opportunities.”

Goy is convinced that the company is still only scratching the surface of the system’s potential yet it has already delivered an impressive range of benefits. “The fact that we measure and know we measure everything has brought company wide accountability and people are taking responsibility for what they do and don’t do.”

Far from being used to punitively check who’s not doing what, the system is actually being used to help identify areas where workers may require further training. “We may have a situation where someone is asked to work on a task with adequate but not the best training. Now we can identify where best practice is happening across our workforce and share that with everyone to help them do their job better. This has helped increase trust in the system amongst the workforce.” He continues, “The more data we collect, the more we can begin to identify trends which lets us move beyond understanding what’s happening and when and to start to uncover underlying reasons which allows us to take preventative measures.”

Another benefit comes from the elimination of the paper trail where information is now 100% visible and useable. “Previously events may have occurred overnight or over a weekend which operators on a morning shift may not have been made aware of,” explains Goy. “Now operators are always working to the latest work-to lists based on the most up-to-date schedule.” When it comes to cost savings, it’s hard to make before/after comparisons because of the unavailability of prior accurate data but Goy estimates a minimum of £1500 per month.