Moving your business closer to becoming a Smart Factory is widely regarded as essential to continuing competitiveness and profitability. Driving efficiency savings, making productivity gains, dealing with skills shortages – these are just some of the challenges that manufacturers face, all of which can be considerably mitigated with Smart Factory solutions.
How do you get to the Smart Factory, though? What should you do next, how far should you go now, and what are the priorities? How do you transform your manufacturing operations into a future factory?
The answers to these and similar questions are not easy as there is no one-size-fits-all solution. Instead, the many different variables that exist mean the solution is different for every production environment.
Those variables include the production inefficiencies that currently exist, issues with productivity, and the specifics of the product/s being manufactured, as well as the wider business processes for procurement, distribution into the supply chain, sales, and more.
Initial Stages
We’ll look at the essential technical steps that are required to move your manufacturing facility closer to being a Smart Factory, but there are some initial stages that you need to go through before any technical work should begin.
Identifying Priorities and Goals
Wherever you are on your Smart Factory journey, it is essential to identify your current priorities and goals. Those priorities and goals could be something specific, such as introducing a new product to your production line or increasing capacity without the need to hire additional staff. These are ideal opportunities to introduce new technologies that will help with your smart factory evolution.
You might also have more generalised priorities and goals where the aim is to improve efficiency, productivity, decision-making, and/or reliability on your existing production lines. This could be, for example, increasing levels of automation to alleviate recruitment or staff retention pressures, or it could be optimising OEE to maximise profitability.
Smart Manufacturing Audit
Another initial stage you should go through is to audit your current Smart Factory status. This audit should include all aspects of your operation, such as the equipment on your production lines, the current level of systems integration, how you use data, your IT infrastructure and the level of integration with OT (operational technology), cloud vs. on-premises systems, and connectivity.
As well as giving you an overview of your current status, an audit will also tell you what can be achieved by implementing new Industry 4.0 technologies and processes. You can then use this information to identify the opportunities that best match your priorities and goals, and that will deliver the best return on investment.
Technical Steps Towards the Smart Factory
The steps typically involved to move your facility from where it is now to a Smart Factory include:
- Enabling communication and the collection of data – this is known as Equipment Systems Integration
- Data visualisation – to make it possible for you to access and process the data collected
- Automated decision-making – where many manual and time-consuming decisions are automated
- Machine learning – where the systems in your facility automatically improve by learning from real-time data and the outputs from previous decisions
Step 1 – Equipment Systems Integration
The ultimate objective of equipment systems integration projects is to connect all potential sources of data to a common system. This includes the production line as a whole as well as individual machines and equipment.
It can also include data not directly connected to manufacturing the product, both within your organisation and outside it.
Within your organisation, this includes data from other units and departments in the business, from finance to HR to purchasing to sales and marketing. This process is known as vertical integration, where the focus is on integrating the OT (operational technology) and IT (information technology) aspects of your business.
Outside your organisation, the main focus should be on your supply chain. This is known as horizontal integration. It involves integrating with third parties in your supply chain both upstream and downstream to achieve real-time visualisation and communication, and to maximise efficiency.
Once systems are integrated and connected to a common system, you can start making changes that will deliver real and tangible benefits for the company. This includes automating additional processes where it wasn’t possible to do so before because the equipment and platforms couldn’t connect or communicate with each other.
Your system will also be able to collect and store data, setting you up to move to the next step.
Step 2 – Data Visualisation
Once you have gone through an equipment systems integration process, your production facility will have the capability to collect data from a vast range of sources.
This is only one step in the journey, however. The real work begins when you start putting the data you collect to good use. In other words, the data your system collects must have value.
After all, data in itself won’t improve your business. You’ll derive value from how you use that data.
Implementing data visualisation solutions is a key part of this process.
Data visualisation makes it possible for decision-makers to make sense of the data collected. Those decision-makers can then act on what the data tells them. This applies to everyone, from operatives to engineers to engineering managers to CEOs.
Again, however, this is only a step on the Smart Factory journey as the next point, automated decision-making, will improve productivity even further.
Step 3 – Automated Decision-Making Based on Data
Automated decision-making is where you move from a position where people analyse and use data to one where the system makes decisions itself. This can be rules-based decision-making, where you have if-this-then-that scenarios, or it can be data-driven decision-making.
Automating decision-making offers a range of benefits:
- Decisions can be taken immediately any time of the day or night as there is no need to wait for a decision-maker to be available
- Improved productivity and enhanced OEE as a result of eliminating decision-making delays
- Eliminating the risk of human error in decision-making
One of the most straightforward examples of automated decision-making is equipment maintenance schedules.
Instead of a manager scheduling maintenance according to a timetable created by the manufacturer of the equipment, sensors collect data with that data then used to determine the best time to schedule maintenance. As a result, maintenance scheduling decisions can be based on specific business objectives, such as conducting the maintenance before a failure occurs or completing the maintenance when it will have the least impact on output.
Step 4 – Machine Learning
Following on from the above, the next step is to enable your Smart Factory to learn from the decisions it takes and the information it receives.
So, in the equipment maintenance example above, the system will learn as the machine operates in the live production environment, tailoring the maintenance scheduling decisions it takes accordingly.
Another technology that becomes important in this part of the Smart Factory journey is statistical modelling and digital twins. These technologies allow you to run data-driven simulations to improve processes, plan for production line changes (such as new product introductions), and more.
Furthermore, machine learning opportunities exist with data from all sources, not just the manufacturing element of the business. For example, a Smart Factory with machine learning capabilities can also improve areas like product development and sales forecasting as it gets better at predicting customer trends and other external factors.
Moving Forward
The above is a general guide to the steps typically required on a Smart Factory development journey. What should you do now, however?
At SL Controls, we can help you answer this question through services like digital maturity assessments, Smart Factory road-mapping, automation strategy development, and creating a business case. Find out more today.