hile Developing an entire ecosystem geared towards quality in manufacturing will help your business to excel from the shop floor, to the top floor. Not only will your products and processes reach new performance peaks – you will unlock everything from faster time to market to greater agility.
Tackle digitalisation
Transformation plans hinge on data. Data hinges on digital rather than analogue outputs. The reality on the ground in manufacturing however is that an incredible amount still depends on pen, paper and
spoken word.
Beyond this, siloed systems and processes are common. This means we are generating pockets of data that we cannot act on or expand upon. So how can we create a full picture of data, put it to work and eliminate places for problems to hide?
Develop a digitisation plan
Start by defining your longer-term technology needs, identifying places where older technology is creating an analogue gap. Conduct a thorough assessment of your current manufacturing processes, equipment and systems. Identify areas that can benefit from digitalisation and prioritise them based on potential impact and feasibility. Assess whether data is being collected, contextualised, stored, shared and leveraged in time to reap actionable insights and deliver value.
Plug analogue gaps
Quantify where processes or equipment are still analogue with a view to digitising. However, do not rush to replace existing machinery that has many further years of reliable use. Existing equipment can be augmented by installing sensors to collect real-time data on performance, temperature, vibration and other relevant parameters.
Develop a robust IT infrastructure
Doing anything clever with data requires clever IT. Beyond the basic fundamentals of high-speed internet, processing power, cybersecurity and data storage capabilities, consider implementing edge computing to process data closer to the source for real-time decisionmaking. Store your data and applications on cloud platforms. This enables remote monitoring, collaboration, and access to realtime data from anywhere, improving agility and flexibility. Implement data collection and storage systems to handle the influx of data. Use data analytics and machine learning tools to process and analyse this data for insights and decision support.
A smart factory is a connected factory – throughout the value chain
Supercharge quality across the value chain
The goal here is to develop a quality digital thread that connects your business, your people and leverages your data for seamless products and processes. Here’s how to do it.
Identify data silos, complete your digital picture
Unless digital tools are helping you to build a fully connected digital picture, they are limiting you at a strategy level. A closed or siloed digital system is essentially an analogue blind spot. Eliminate them by assessing the openness and interoperability of software across your value chain. Identify and then connect any tools that are open and interoperable to rapidly add detail to your digital picture of operations. Then identify where proprietary or closed source products are limiting your ability to create a seamlessly connected ecosystem. Finally, work with your teams to develop a plan that eliminates data silos and digital gaps.
Create a digital feedback loop
A fully digital manufacturing process enables the creation of an
information system with a feedback loop. This gives you the data you need to simulate the end-to-end process, identifying and mitigating issues before they occur. This is the foundation piece for any smart factory.
Harness the benefits of a Quality Management System (QMS)
A QMS platform will allow you to drive value and profitability at an operational level across the value chain, enhancing efficiency, compliance and profitability.
Shift left
Look earlier in the process to make quality gains. High quality products and highly efficient
production both start with great design. Empower your design teams with data from the make and inspect phases, and harness generative design and digital twin to refine your product designs with quality in mind.
Connect top floor and shop floor systems with a system of engagement platform
You need a single central place where you can visualise the data you are generating across the design, make, inspect and business cycles, by persona, from shop floor to top floor. True digitalisation is characterised by completeness, openness and the ability to harness and deploy insight. Here manufacturers need a system of engagement platform that enables them to manage all of their ecosystems from one place. Layering this with AI then generates insight to truly transform products, production and deliver against your business outcomes. Explore Hexagon’s Nexus digital reality platform here.
Digital twin
Develop digital twins of your manufacturing processes, equipment and facilities. These virtual replicas allow you to simulate and optimise processes before making changes in the physical environment, reducing risks and improving efficiency. Read more about how to get started with digital twin here.
Prioritise openness in procurement
Work with technology providers who guarantee openness and interoperability with your existing technology.
Design, make and inspect business functions are not individual islands but fundamentally connected elements of a shared environment
Create an environment for seamless collaboration
There’s a difference between eradicating data silos and collaborating. In today’s factories people work with people, robots and geographically distributed teams as well as suppliers. How can manufacturers connect the dots both within and outside the organisation? Improving collaboration is a huge opportunity so let’s help you seize it:
Root out collaboration issues with an audit
Most organisations experience collaboration challenges in different places and for different reasons. Make sure you identify your own specific weak points. Taking a view across the various steps of the value chain, you should assess how well information is being shared, how well teams collaborate, and
what may be holding them back. Is it a lack of technology, poor integration, geographical
distribution of teams or something else entirely. Knowing where the gaps exist is the basis for a target-oriented solution.
Promote data sharing
Establish protocols for data sharing across departments and with suppliers. Move from a siloed approach towards a more open, transparent workflow where people are able to view, edit and share
different file types without blockers creating issues. All key data should be aggregated in one place, available in real-time, providing a complete overview of the manufacturing process to all relevant stakeholders.
Break down the walls
Prioritise inter-team and cross-team initiatives that break down departmental walls. Make every effort to ensure remote workers feel connected to their team and the wider organisation. Encourage diverse perspectives and cross-functional cooperation to drive innovation.
Restructure workflows and leverage connected worker tools
Humans do not naturally work in synchronisation, we need a layer of structure, or a means of orchestration to reach peak performance. Adopt tools and restructure workflows to support dynamic
and responsive working, both within and between teams. Connected worker solutions harness knowledge from across the business – learning, evolving and improving from digital and human inputs. This means you can optimise workflows, maximise productivity and digitise the time-earned expertise of your longest-serving engineers while harnessing the digital skills of career entrants.
Invest in automation and AI
Automation technologies can reduce the burden of routine tasks on skilled staff, freeing people to focus on more value-adding activities such as new product development, collaborate with peers and work on projects that deliver better business outcomes in shorter timeframes.
Harness the potential of automation
Automation is an important driver of quality. On a robotics level it eliminates human error increasing repeatability and scalability, while on an inspection level it scales efficiency. On a systems level, AI can mine your data for insights, making recommendations that transform performance across your business. Here’s how to:
Invest in employee skills
Develop a plan to upskill existing staff so your team understands how to leverage automation technology for better organisational efficiency and productivity.
Identify automation gaps
Conduct an audit to help you identify where automation could help your business to save time, improve safety and lift quality standards. Establish a working group to plan the integration
Successful automation requires everything from shop floor engineering expertise to IT systems know-how. Across function team should be established to develop an automation plan that considers how new technologies will work alongside and integrate with existing technologies.
Close the loop with automated inspection
Automated inspection dramatically reduces the amount of time setting up jobs freeing up the valuable time of skilled workers. Look for solutions that go beyond robotics. The latest inspection cells driven by the latest AI powered software, quickly learn how to set up jobs, learning essential things from your engineers to safeguard knowledge. Richer insight from the inspection process can be used to close feedback loops with design.
Turn data into action
With clean, complete data, AI can quickly compare and contrast diverse and disparate sets of data that
would take a human days, weeks, months or even years. Pinpointing problems that would never otherwise have been detected, AI can now go beyond making recommendations. Digital assistants extend AI into the realm of performing tasks. In manufacturing, digital assistants can be used to enact AI recommendations, streamline complex processes and create more productive workflows for people and equipment. Digital assistants are a major step towards automation and smart technology. Within the factory, they are an excellent tool for operational efficiency driving predictive maintenance, quality control and anomaly detection by creating circular feedback loops.
Use edge computing
For more data-intensive tasks or where real-time processing is critical, consider using edge computing. It processes data closer to where it is generated (the ‘edge’ of the network), reducing latency and increasing speed of response in automated systems.
Cloud processing
Greater automation will see you running more software, more analysis and more simulations, so you need greater and more scalable processing power. The processing capabilities of cloud infrastructure allow you to monitor and optimise your automated processes in real-time, driving efficient production.
Stay secure
As automation often involves networked technologies, it’s crucial to shore up cybersecurity measures. This could mean updating software, enhancing access control, or employing cybersecurity specialists to
manage and mitigate risks effectively.
We hope the advice outlined in this report helps you to accelerate your transformation planning. If you would benefit from further support, please reach out to our team of experts who will be happy to assist.
