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How your level of servicing is affecting the bottom line

The pressure is on manufacturers to meet greater demands, deliver on time, within budget and work to regulations – all while keeping costs as low as possible.  In the manufacturing context, a good service regime should be in place to avoid costly downtimes and keep the lines running optimally. 

When a downtime does occur, (usually at the worst possible time), the expertise and responsiveness of your service provider to get you back up and running, allowing you to fulfil your obligations, can either make or break your bottom line.  

Of course, there are different levels of service, and you get what you pay for, but broadly they are split into three groups:

  1. Reactive Service:

Most likely we’ve all been a ‘reactive customer’ at some point in our lives – for example, the washing machine breaks down and, although an inconvenience, it’s not going to cost us a fortune.  For manufacturing it is very different.  This is where rapid response time for technical support and the ability to get a nearby field engineer to site is vital to minimize a costly delay.

  1. Proactive Service:

How beneficial would it be to your bottom line to have your service needs anticipated?

Well, with proactive service this is just what happens.  If you choose a service agreement (and when you add up the cost of downtime, it’s a no-brainer), the system can provisionally book your required printer service and send you an email notification leaving you to accept or change the appointment as you wish.   Routine maintenance is carried out in a timely manner, fluid stock levels are maintained by agreed delivery schedule and key spares are kept on site for immediate deployment - keeping outlay and disruption to a minimum.

  1. Predictive Service:

Most of us will have heard of the Internet of Things (IoT) or the Industrial Internet of Things (IIoT).  Fundamentally this is where we now have the ability, through interconnectivity, for devices to ‘talk’ to cloud applications, each other and to the operator.  So, IIoT can flag when a line is more likely to go down before we have noticed the signs ourselves or, in other words ‘anticipating unplanned events’. 

Having the data to alert us to a potential unplanned event and fix it before it becomes a real issue, has a massive, positive effect on downtime and the bottom line.

IIoT will be discussed in more depth in the next blog.

So, why is downtime such a problem?   

Industry estimates are that almost every factory loses at least 5% of its productive capacity from downtime, and many lose up to 20%.  

The main causes of unplanned downtime include equipment parts failures, human error, operating in a high output environment (running lines too fast and for too long), technical issues (mechanical or electronic), and small intermittent stoppages.

What makes up downtime costs?

It should be borne in mind that downtime is not just the obvious tangible costs such as lost capacity, lost production, direct labor costs and inventory that are relatively easy to put a figure on.  There are also the fines from late deliveries, levied by large retailers when manufacturers fail to deliver as promised.

Then there are the far-ranging intangible costs, such as damage to the customer relationship, reduced loyalty and long-term damage to your brand reputation – along with staff stress and mental health implications, and even damages the ability for organisations to be agile and innovate.  These may be difficult to quantify, but may be even more significant than tangible costs. 

How can we measure downtime?  

Although notoriously difficult to measure, there are two main methods:

  1. OEE

oee.com defines it as: the percentage of manufacturing time that is truly productive. An OEE score of 100% means 100% Quality (only good parts), 100% Performance (as fast as possible), and 100% Availability (no Stop Time). 

    2. Downtime calculation is the loss of revenue over downtime ie. number of products produced per hour, along with the revenue made on each item.

So, if 1000 units are produced each hour, at a cost of $2 each, then each hour of downtime is worth $2000. 

It is easy to see how quickly costs stack up when the downtime goes on for longer and where more is produced each hour. 

It is vitally important to keep downtime to a minimum – the tangible and intangible costs make it worth addressing and putting in preventative measures.  This starts right at the beginning, when purchasing the equipment.  Of course, competitive pricing is important, but consider the whole package including the level of service you will receive further down the line. 

If you would like more information on the types of service Linx can offer, and how we value uptime, get in touch with a member of our Linx Team.

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