How many times has downtime come up for you as a costly challenge to be addressed in the last month?
Like a broken record, time and time again we’re reminded that downtime is costing us. It’s a drain on the productivity of every manufacturing business. Is it something you’ve just come to accept as the cost of doing business or are you seeking options to reduce downtime with solutions that generate fast and ongoing ROI?
The reality is downtime is expensive — arguably the single biggest contributor to production and profitability losses for manufacturers. In fact, downtime costs UK manufacturers a whopping £180bn a year. But where do these figures come from, what are the root causes of downtime, and most importantly what’s the easiest way to minimise it?
So we’re on the same page — downtime is literally whenever a machine is ‘down’ — that means sitting idle or not producing anything. This is bad for a number of reasons, but most obviously: if your machine isn’t creating products, then you have no products to sell and you’re making no revenue. The higher the downtime the poorer your asset utilisation and the lower your productivity. When you look into things more deeply however, the actual reasons machines are in downtime can raise some serious red flags that deserve investigation. Fine if a machine is down due to scheduled maintenance (another really important topic — stay tuned for our article on this in the coming weeks), but when you’re stopping machines for an unplanned reason like tool changeovers, machine/silo failure causing unexpected maintenance, waiting on raw materials, operators away from their stations, or product quality issues — then production is suddenly halted due to a reason that has deeper-seeded operational consequences.
The difference between planned downtime and unscheduled downtime is one that is really important to get right. Unplanned downtime is exponentially more expensive, and eats the heart out of the bottom line. Deciding when a machine should be repaired or replaced instead of the machine or process deciding for itself, is going to save you a lot of headaches and a lot of money. Costs for parts and labour really are just the beginning for faulty machinery — excessive energy consumption, wastage, lost production and missed deadlines quickly compound into huge deficits.
As put by Salman Taghizadegan (PhD Chemical and Plastics Engineering, and Operational Excellence Director at Laird Connectivity) in his book Essentials of Lean Six Sigma:
“The goal is no machine downtime, zero defects, maximum machine lifecycle and throughput, customer satisfaction, and the bottom line. Basically, the goal is to prolong production performance until it reaches a point that the machine requires complete replacement due to wear and tear or technology change, if justified.”
Granted — but how do you go about this?
The first step is to stop looking at machine downtime in isolation. Once you start to break down the reasons for downtime you begin to see there isn’t a single solution — and that success will come from a holistic approach to manufacturing. Let’s revisit our list of downtime reasons from earlier:
1 — Tool changeovers
Simply put, machines need the correct tooling to operate effectively. We all know this, so why is it so hard to plan for tool changes and ensure your workers have everything they need, well ahead of time, to make these changes as fast and efficient as possible?
More often than not, the reason is human error, with the majority of delays to manufacturing deadlines attributed to this source. It’s difficult enough for planners to schedule tool changes, let alone have all the equipment ready and align the many workers and suppliers on time and at the right place to make this a speedy process. It’s a bit like a pit crew in a car race — the team needs to have all the tools they need to hand, have practiced and prepared for the pit stop, and be warned well in advance of the incoming car to make the stop as fast as possible.
The great thing is that with today’s technology you don’t have to rely on planners to herd all these cats, the machines themselves can detect and notify everyone involved of the tool change — well before the event itself. How? These days manufacturers can install affordable, Internet of Things (IoT) devices into existing machinery in their factories — regardless of age, make or model — and get real-time, actionable insights. In this case, the insight is when exactly to expect a tool change, and the action is to automatically notify and prepare the workers responsible for it ahead of time.
As put by José M. Guerrero in his book Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering (2020):
“The purpose of IoT is to use sensors in physical devices to monitor and control them. This technology is fast becoming the norm — by the year 2020, the IoT will comprise more than 30 billion connected devices.”
While IoT is a fantastic resource for manufacturers, without a way to decipher the information garnered by these sensors and interpret it into actions, it’s incredibly difficult to know what to do with the mountains of data collected each day by IoT. Platforms like ThingTrax utilise the capabilities of Artificial Intelligence (AI) to convert this data into easy to interpret reports, that allow decision making and benchmarking performance across sites in real time to be fast and simple.
2. Machine/silo failure causing unexpected maintenance
Understandably when things get used over and over again, wear and tear inevitably results in things breaking. In fact, equipment failure is the cause of 42 percent of this unplanned downtime and it’s no surprise that in this case, prevention is the best cure. Just like with tool changes, maintenance can also be predicted, planned and completed well before wear and tear leads to costly breakdowns that bring production to a grinding halt. And just like tool changes, IoT devices and AI can manage the whole process automatically, planning the maintenance for a time which won’t interrupt output, with no human error in scheduling.
3. Waiting on raw materials
To paraphrase the first law of thermodynamics ‘you can’t make something from nothing’, and the same is true in manufacturing: A machine cannot create products without raw materials to make them from. The key to maximising output is to ensure your machines are continuously stocked with the materials they need, the entire time they’re running. Overall equipment effectiveness (OEE) plummets when machines sit idle waiting for materials (as does energy efficiency — more on that in a coming article), so it’s well worth addressing your material routes from storage to silo to machine before you’re hemorrhaging electricity costs and missing job deadlines. Once more, tech is your friend here and can do a lot of the heavy lifting to ensure machines are continuously stocked without much thought or effort from your staff. Again, IoT devices can monitor raw materials and notify workers at the most optimal time to restock the machine before a lack of material stalls production. An extension of this is that the same sensors can also monitor stock in silos and storage areas, automatically ordering additional material from suppliers to top up your overall supply as needed. Want to go that next step further in removing human error? When material runs low a signal can be automatically sent to a robot on the factory floor, who will retrieve raw materials and deliver them to the machine before the operator has even noticed there’s a need to resupply it.
4 — Operators away from their stations
So you’ve got the right tools, the machine has been regularly serviced and is fully stocked with raw material — nothing is going to stop your machine from achieving optimal output. That is, until your workers step out for a nice extended lunch break and your machine is left with no one to operate it. Sadly, this is the case far too often and the reality is that site managers simply can’t keep an eye on everyone at all times — or can they?
ThingTrax can actually tap into CCTV across the entire factory or fixed cameras at machine or manual work stations and use the video data to notify managers if zones on the factory floor are unmanned for longer than a set period of time. Facial recognition software can even inform the manager exactly who is missing from their station so there’s no more scrambling around trying to find the right worker for the right job and get them back where they’re supposed to be as fast as possible (in fact, ThingTrax’s operator skills matrix can improve job assignments based on worker skills & identify employee training gaps — though this is a topic for a future article). Conversely, downtime can also be caused by too many workers crowding zones in a factory. This too can be monitored by sensors that create infrared heat maps of the factory floor to detect spikes in heat caused by congestion (or fire, if hot enough) and notify managers to redirect staff for a safer work environment.
Often we see screens in factory break rooms tracking uptime and production levels, and this is a good start, since a focus on this helps employees not just be aware, but build a healthy competition between shifts. The next step for manufacturers however is to provide workers with clear actions from those numbers, and make it easy to understand the steps they can take to win that competitive edge.
5 — Product quality issues
Understandably, a machine should be switched off right away if the products it is creating are faulty. Poor product quality is another leading contributor to machine downtime and is caused by issues with temperature, pressure, humidity and faults in the raw material fed to the machine to name a few — each of which needs to be monitored constantly. Not only to avoid the machine going into downtime, but also to maintain the optimal temperature and pressure to produce as many units per hour as is possible by that machine. Without IoT devices, quality and wastage monitoring is an extremely manual process, with workers physically inspecting faulty products and attempting to determine the cause by eye. This can take a lot of troubleshooting to figure out, and therefore is one of the lengthiest resolution processes for downtime. Fortunately once again, IoT devices and LiDar sensors have the capability to analyse and report on all of those factors, in real time and with no human error. Analytics and insights derived by artificial intelligence can help operators set parameters perfectly, limiting the cause for defects and wastage.
To summarise — tool changeovers, machine/silo failures causing unexpected maintenance, delays in the delivery of raw materials, operators unskilled or away from their stations, and product quality issues all contribute to downtime, and to succeed in resolving these, manufacturers must stop looking at these in isolation and instead consider a holistic approach to optimisation. Implementing solutions can often be put off because it’s presumed that it will take too long, it will cost too much, or it will be too complicated to implement or adopt. As a result, it’s common to cope with the status quo even though it’s costly and practical solutions are available. The reality is that smart manufacturing solutions like those listed in this article are both affordable and quick to implement — with IoT devices able to be installed in less than a day to existing machinery — no matter the age, make or model — with no disruptions to production.
At ThingTrax every one of our customers have been able to cut downtime at their factories by at least 30% — if you want to know how to achieve the same result for your sites, simply input your challenges into this form, and one of our Factory Advisors will come back to you with a list of solutions tailored specifically to your factory needs.
Or, if you want to see ThingTrax in action first, book a free trial with us here, where we’ll connect your factory and give you access to real-time analytics and insights from your own machines in less than a day. The time is now to invest in the digital tools that will transform your business and the technology to drive continuous improvements for your factories well into the future.
