Lee Sullivan, regional sales manager at industrial software provider COPA-DATA UK, explains the steps manufacturers must take to boost ROI using Big Data.
According to research from Barclays Corporate Banking, over half of the manufacturers are reporting improved productivity thanks to the adoption of Industry 4.0 technologies. Despite this, two-thirds state that they are yet to experience a return on investment (ROI).
ROI is a priority for manufacturing. However, making radical changes to a factory is not always a feasible option. A complete systems overhaul, for instance, could be the quickest and most straightforward way to optimise production. However, it can be incredibly costly and comes with high risk, and possibly long periods of downtime — not to mention the cultural challenges that accompany a shift in how a factory operates.
Instead, most factories will choose to make small incremental changes to increase their overall equipment effectiveness (OEE) and, in turn, improve their ROI.
Identifying constraints
The process of improvement usually begins by recognising the limitations in the factory or within certain processes. This could be related to plant production time or plant performance management, equipment failures, product defects or even a lack of human skills to manufacture. However, without hard data, identifying these constraints can be time-consuming, if manually completed, and complex. Therefore, software is recommended to simplify the process.
Monitoring and data acquisition software can quickly identify baseline figures for major losses in throughput across the production plant or the product manufacturing process. This data should be collected over a set period. From here, manufacturers can identify the most critical or valuable place to start improvements.
Following the deployment of software to collect this baseline data, the manufacturer can compare OEE results against real data and historical reports and begin a continuous improvement (CI) process.
CI, of course, is not a new phenomenon, but digitisation of lean manufacturing losses is. This would enable easy analysis and correlation with productions figures, showing potential areas for improvement in a factory which in turn will help to increase ROI.
Reducing waste for ROI
Being able to monitor OEE, total productive maintenance (TPM) and CI would highlight potential areas for improvement, but also identify whether improvement projects established have facilitated the manufacturing process. For example, a measurable indicator which can lead to improved ROI.
Waste reduction is an example of CI. This term describes the non-value-added wastages that absorb time and money. Eliminating waste is a vital part of the lean manufacturing methodology and is often the first step to improving processes.
Using monitoring software, these wastages can be digitalised and monitored, offering manufacturers the knowledge to minimise poor quality. In fact, a COPA-DATA customer in the automotive industry was able to save 5 per cent on man-hours per employee using digital fault logging.
Take the waste of waiting as an example. In a manufacturing facility, this could describe a halt in production due to a delivery delay, unplanned system downtime or wasted minutes or hours due to poorly planned production schedules.
Using software, this waste can be digitally recorded and reported, identifying the reasons why a delivery has not arrived, why certain machines are not hitting their cycle times or when pieces of equipment are entirely idle.
Waste reduction can also be achieved by using software for statistical process control (SPC) reports, a method of measuring and controlling quality during manufacturing. Naturally, well-defined production and product processes will reduce scrap waste. Cutting down variability will not only improve quality in assembled parts but could reduce customer complaints and improve sales through customer satisfaction.
COPA-DATA’s industrial software, zenon, can generate SPC reports automatically, recording process capabilities which, in turn, shift factories towards boosting ROI.
Starting small
Increasing ROI may be a priority for manufacturers but investing heavily in a software overhaul can be daunting. A dramatic overhaul not only generates risk but could create cultural challenges for the plant.
COPA-DATA’s zenon is fully scalable. This means that end users do not need to jump straight into the deep end and deploy the software on every value stream area. They could begin with a smaller system, such as capturing downtime and throughput.
Upon analysing the results of this metric, manufacturers can begin to measure other areas for improvement, such as production quality, CI projects, mobile connectivity, recipe groups, or even begin vertical integration by linking the software to enterprise resource planning (ERP) systems and cloud solutions.
Manufacturers expect to experience a rapid ROI after adopting new technologies — whether it be robotics, automation, sensors or enterprise software. According to Barclays Corporate Banking research, these investments are reaping productivity rewards for manufacturers. However, without identifying areas for improvement, how can manufacturers optimise their facilities to their full potential?
The answer is in their data.
ROI as a goal in the smart factory
Lee Sullivan, regional sales manager at industrial software provider COPA-DATA UK, explains the steps manufacturers must take to boost ROI using Big Data.
According to research from Barclays Corporate Banking, over half of the manufacturers are reporting improved productivity thanks to the adoption of Industry 4.0 technologies. Despite this, two-thirds state that they are yet to experience a return on investment (ROI).
ROI is a priority for manufacturing. However, making radical changes to a factory is not always a feasible option. A complete systems overhaul, for instance, could be the quickest and most straightforward way to optimise production. However, it can be incredibly costly and comes with high risk, and possibly long periods of downtime — not to mention the cultural challenges that accompany a shift in how a factory operates.
Instead, most factories will choose to make small incremental changes to increase their overall equipment effectiveness (OEE) and, in turn, improve their ROI.
Identifying constraints
The process of improvement usually begins by recognising the limitations in the factory or within certain processes. This could be related to plant production time or plant performance management, equipment failures, product defects or even a lack of human skills to manufacture. However, without hard data, identifying these constraints can be time-consuming, if manually completed, and complex. Therefore, software is recommended to simplify the process.
Monitoring and data acquisition software can quickly identify baseline figures for major losses in throughput across the production plant or the product manufacturing process. This data should be collected over a set period. From here, manufacturers can identify the most critical or valuable place to start improvements.
Following the deployment of software to collect this baseline data, the manufacturer can compare OEE results against real data and historical reports and begin a continuous improvement (CI) process.
CI, of course, is not a new phenomenon, but digitisation of lean manufacturing losses is. This would enable easy analysis and correlation with productions figures, showing potential areas for improvement in a factory which in turn will help to increase ROI.
Reducing waste for ROI
Being able to monitor OEE, total productive maintenance (TPM) and CI would highlight potential areas for improvement, but also identify whether improvement projects established have facilitated the manufacturing process. For example, a measurable indicator which can lead to improved ROI.
Waste reduction is an example of CI. This term describes the non-value-added wastages that absorb time and money. Eliminating waste is a vital part of the lean manufacturing methodology and is often the first step to improving processes.
Using monitoring software, these wastages can be digitalised and monitored, offering manufacturers the knowledge to minimise poor quality. In fact, a COPA-DATA customer in the automotive industry was able to save 5 per cent on man-hours per employee using digital fault logging.
Take the waste of waiting as an example. In a manufacturing facility, this could describe a halt in production due to a delivery delay, unplanned system downtime or wasted minutes or hours due to poorly planned production schedules.
Using software, this waste can be digitally recorded and reported, identifying the reasons why a delivery has not arrived, why certain machines are not hitting their cycle times or when pieces of equipment are entirely idle.
Waste reduction can also be achieved by using software for statistical process control (SPC) reports, a method of measuring and controlling quality during manufacturing. Naturally, well-defined production and product processes will reduce scrap waste. Cutting down variability will not only improve quality in assembled parts but could reduce customer complaints and improve sales through customer satisfaction.
COPA-DATA’s industrial software, zenon, can generate SPC reports automatically, recording process capabilities which, in turn, shift factories towards boosting ROI.
Starting small
Increasing ROI may be a priority for manufacturers but investing heavily in a software overhaul can be daunting. A dramatic overhaul not only generates risk but could create cultural challenges for the plant.
COPA-DATA’s zenon is fully scalable. This means that end users do not need to jump straight into the deep end and deploy the software on every value stream area. They could begin with a smaller system, such as capturing downtime and throughput.
Upon analysing the results of this metric, manufacturers can begin to measure other areas for improvement, such as production quality, CI projects, mobile connectivity, recipe groups, or even begin vertical integration by linking the software to enterprise resource planning (ERP) systems and cloud solutions.
Manufacturers expect to experience a rapid ROI after adopting new technologies — whether it be robotics, automation, sensors or enterprise software. According to Barclays Corporate Banking research, these investments are reaping productivity rewards for manufacturers. However, without identifying areas for improvement, how can manufacturers optimise their facilities to their full potential?
The answer is in their data.
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