Manufacturing Analytics For Automotive Manufacturers Software

In 2022, Forbes reported how ‘unplanned machine downtime’ (poor productivity) has a massive impact on a factory’s overall efficiency and profitability. It stated that the average manufacturer confronts 800 hours of equipment downtime per year — more than 15 hours per week. 

Downtime is not cheap! For example, the average automotive manufacturer loses $22,000 per minute when the production line stops.

When put into perspective, FourJaw's downtime monitoring software is a small investment with a huge return, and offers automotive manufacturers a simple way to save a lot of money.

FourJaw's advanced machine monitoring solution is designed for use on all types of manufacturing equipment and is suitable for factories of all sizes. 

In the automotive industry, our analytics software is frequently utilised on:

• CNC Lathe

• CNC Turning

• CNC Milling

• Drilling

• Oxy-fuel cutting machines

• Laser Cutting

• Waterjet Cutting

• Plasma Cutting

• Conveyor

• Inspection

• Packaging 

• Weighing

Learn more about CNC machine monitoring with FourJaw.

There are generally two main types of automotive manufacturing: automotive parts manufacturers, which can be independent machine shops that make car parts/accessories for the aftersales market (for example, Cobra Sport), and larger automotive parts manufacturers that manufacture parts for the automotive brands (OEMs). Examples of multinational automotive part manufacturers include Goodyear and Bosch.  The second is the automotive brands themselves: think of the likes of Honda, Toyota and the world’s biggest automotive manufacturer (by revenue) Volkswagen group.

Machine monitoring provides manufacturers with full factory floor visibility of how well machines are being utilised, by showing the machine downtime and uptimes.

With the FourJaw machine monitoring platform, operatives can categorise the reasons for the downtimes so factory floor managers get a clear picture of how productive the machines are. Here's a useful case study that shows how a manufacturer improved their machine utilisation by 400%. 

Yes. Our machine monitoring platform was specifically designed to make machine monitoring accessible to manufacturers of all shapes and sizes, which of course meant we designed our platform to work with any type of machine, regardless of age, brand or model. So you can turn your 50-year-old machine into a 'smart machine', helping you to understand how productive your machines are. 

Although not specifically designed to reduce energy usage, machine monitoring software can help factories reduce their energy usage indirectly and therefore become more efficient and sustainable. 

Because our machine monitoring software reports on your machine utilisation, by machine, cell or factory, the data allows you to see when a machine is being run but doesn't need to be, i.e. wasting energy. By identifying 'negative machine downtime' we have helped a number of manufacturers reduce their production costs, thanks to the data insight FourJaw machine monitoring provided. 

No. Unlike traditional machine monitoring solutions, we designed our machine monitoring platform to be accessible, not only did we make it easy to install (minimising disruption to your shop floor) but we also made it affordable.

We offer monthly payment plans and you can install it yourself, so there are no high upfront installation costs often associated with traditional machine monitoring solutions. Find out more about the pricing plans we offer here. 

Utilisation Data

FourJaw starts with utilisation data in it's simplest form. The specially designed MachineLink hardware is a combination of miniature computer and current clamps. These two current clamps are typically attached to the total power incomer of the machine and the main drive unit, for example a spindle motor of a CNC machine.

This raw data is recorded every second and sent to our secure Azure cloud platform. The data is then instantly built into chunks of running and not running data, typically over 20-second periods, which is then displayed and categorised throughout the FourJaw platform.

What this provides is a very accurate measure of when the productive part of the machine experiences load and when it does not. Applied to this data is FourJaw's Machine Learning program which automatically classifies the data into productive/active and idle/inactive time. This means warm up runs and free air cycles are classed as idle time in the case of a CNC machine as the machines is not in its productive state.

Downtime reasons are inputted by the operator of the machine via a tablet which is installed beside the operator.

Each tablet is paired with a machine via the same FourJaw portal running on a Chrome browser.

When the MachineLink hardware, detailed above, measures a set period of idle time a pop-up appears on the platform asking the user to log why the period of idle time has occurred, this can be inputted straight away, during the downtime or even post the downtime if required.

Yes it does. 

Work order information can be inputted manually or directly imported from a .CSV file.

This data includes the WO number, operations, machine names, estimated job time and start dates.

As with all parts of the FourJaw platform, this data is combined with the downtime and utilisation data to provide meaningful and actionable insights into your production process.

As a manufacturer, it's highly likely you'll already be monitoring Work order times, Ops times and setup times, of course, this is all useful, however, it does not give you the big picture.

For instance, it doesn't identify and inform you of what improvements can be made to improve shop floor productivity.

Machine monitoring differs because it will give you real-time, actionable shop floor data such as:

• Top 5 downtimes, per factory, cell or machine
• Pareto plots
• Average setup time per part
• Downtimes and machine active times per work order

This information can be used to take decisions based on fact and not opinion. I