5th step of Digitalisation - Change The Culture - Become A Smart Factory
The journey towards smart manufacturing is more than just adopting new technologies; it's about integrating various digital layers to create a fully optimised, intelligent factory - A Smart Factory. It’s a culture change in the company of how things are done from here on forward. Each step in the digitalisation process before contributes to moving away from paper and excel towards digitalisation. By combining data collection, manufacturing data analytics and making sense of this real-time data using production scheduling software, you can achieve a seamless, fully digitalised environment.
This integration is the key to driving efficiency, reducing costs, and maintaining competitive advantage. This is where the most value comes to everybody from factory shop floor to C-level. Imagine no more fire fighting for the technical manager, trends of increased efficiency and smoother people management for Production managers. How about people training and recognition for HR? This goes all the way to the top by enabling CEO-s to notice trends and make the best strategic desicions not to mention bonus reports and accurate production prices to the CFO-s. Sounds good? Okay.
Recap of the Digitalisation Steps So Far
Step 1: Connectivity through Manufacturing Data Collection and OEE
Overview: Gathering accurate data is the foundation of any digitalisation effort. GlobalReader’s hardware, including sensors and the Scoutbox, helps manufacturers collect critical data on machine performance and production efficiency.
Internal Link Opportunity: Direct readers to the article on data collection to learn more about how to start their digitalisation journey with effective data gathering.
Step 2: Manufacturing Data Analytics – Visibility and Reporting
Overview: Once data is collected, it needs to be analysed and made actionable. GlobalReader’s Smart Live View and Analytics tools provide real-time data visibility and reporting, allowing manufacturers to understand and optimise their operations.
Internal Link Opportunity: Link to the article on data visibility and reporting to provide a deeper understanding of how to interpret and use collected data effectively.
Step 3: Real-Time Data in Manufacturing - Transparency and Predictability
Overview: Real-time data enhances transparency and predictability on the shop floor. The GlobalReader Operator Tool offers live updates and predictive analytics to ensure smooth and efficient production processes.
Internal Link Opportunity: Guide readers to the article on transparency and predictability to explore how real-time data can transform their manufacturing operations.
Step 4: Production Scheduling Software - plan ahead what is going to happen
Overview: GlobalReader’s Production Scheduling Software help manufacturers anticipate and prevent disruptions. The Planner streamlines production scheduling by allowing easy order entry, workstation assignments, and resource management. Meanwhile, the Maintenance tool uses real-time performance data to predict equipment maintenance needs, allowing you to schedule repairs proactively and avoid unexpected downtime.
Internal Link Opportunity: Direct readers to Planner and Maintenance for a deeper understanding of how both tools enhance predictive capacity.
Step 5 - Change The Culture - Integrate and Adapt
Creating a smart factory requires more than just implementing individual digitalisation steps; it’s about integrating these steps into a cohesive Manufacturing Execution System MES where each layer complements and enhances the others. By combining data collection, analytics. real-time visibility and predictive manufacturing software tools into your Enterprise Resource Planning (ERP) system, there is a powerful opportunity to achieve a seamless, fully digitalised environment that maximises efficiency and productivity.
The Power of Integration:
Combining all four layers needs integration and adaptability. GlobalReader’s systems integrate smoothly with your ERP although can be used as stand alone and still offer fast results. Starting from the 1st step of digitalisation and following through each step gets you closer and along the way earns you more profit.
But this, 5th step, is the stage where your factory can benefit from machine learning and AI in general. We have said before that all manufacturing companies are inefficient and even if you make the right call and take the 5 steps of digitalisation you will still have challenges and problems to solve. You just have more resources now because your factory is efficient and a fully digitalised Smart Factory.
Now, this will not be easy! As you shift away from paper and excel as well as fire fighting mentality in your shop floor there is a lot of explaining to do amongst your staff. The key is to train people, manage them better and find recognition points - work together. It does not always mean that C-level personnel are untouched by this. Often the culture change has to start from the top. Luckily we provide every help, consultations and training along the way.
This integrated approach ensures that every component of the factory is interconnected and working towards the same goal: improving efficiency, reducing downtime, and enhancing product quality. With all layers functioning together, a smart factory can quickly adapt to changes, predict future needs, and maintain a competitive edge in the market. Why, you might ask? Only then can you really add machine learning to find abnormalities outside the norm. Remember we said you are not free from challenges?
What is a Fully Digitalised Factory ShopFloor?
A fully digitalised factory shop floor is a modern manufacturing environment where advanced technologies, such as machine learning in manufacturing, are integrated into every aspect of production. Unlike traditional setups that rely heavily on manual processes and human intervention, a digitalised shop floor uses real-time data, automation, and intelligent systems to optimise operations continuously.
Key Features of a Fully Digitalised ShopFloor:
Integrated Systems: All machines and equipment are connected through a network that allows seamless data exchange and communication. This integration enables better coordination and efficiency across the entire production line up to your ERP.
Automated Processes: Automation plays a crucial role in a digitalised factory. Robots and automated systems handle repetitive tasks, reducing the need for manual labour and minimising the risk of errors.
Real-Time Monitoring and Reporting: A digitalised shop floor uses sensors and data analytics to monitor production in real time. This capability ensures that any issues are quickly identified and addressed, preventing downtime and maintaining high levels of productivity.
The shift towards a fully digitalised factory shop floor is driven by the need for greater efficiency, flexibility, and competitiveness in manufacturing. By leveraging machine learning in manufacturing, companies can move beyond simple automation and real-time monitoring, using data-driven insights to continuously optimise processes and predict future challenges. This evolution marks a significant step forward in the journey towards smart manufacturing, where every decision is informed by accurate, real-time data and advanced analytics. By the way do you remember the difference between digitalisation vs digitisation?
The Role of Machine Learning in a Digitalised Shop Floor
Machine learning in manufacturing is transforming how factories operate by enabling systems to learn from data and find deviations from normalities. Unlike traditional automation, which follows predefined rules, machine learning algorithms can analyse vast amounts of data, identify patterns, and improve over time without human intervention. This capability makes machine learning a vital component of a fully digitalised factory shop floor.
How Machine Learning Works in Manufacturing:
Data Analysis and Pattern Recognition: Machine learning algorithms analyse real-time data from various sources, such as sensors and production equipment, to detect patterns and anomalies. For example, if a machine shows signs of wear, the algorithm can identify the pattern and predict when maintenance is needed.
Predictive Maintenance: One of the most significant benefits of machine learning is its ability to predict equipment failures before they occur. By monitoring machine performance and identifying potential issues early, manufacturers can schedule maintenance at optimal times, reducing downtime and extending the lifespan of their equipment.
Process Optimisation: Machine learning helps optimise manufacturing processes by continuously analysing data to find the best operational settings. Whether it's adjusting machine speeds, temperatures, or other variables, machine learning algorithms can fine-tune production to achieve maximum efficiency and quality.
Integrating machine learning in manufacturing allows companies to move beyond reactive problem-solving and adopt a proactive approach to managing their operations. By leveraging machine learning, manufacturers can predict and prevent issues, optimise processes in real time, and ensure consistent quality across the shop floor. This advanced technology is key to achieving a truly digitalised and smart factory environment.
How GlobalReader Integrates Machine Learning into the Shop Floor
GlobalReader uniquely harnesses machine learning in manufacturing to optimise operations and drive continuous improvement on the shop floor. By embedding advanced machine learning algorithms into its suite of tools, GlobalReader allows manufacturers to not only monitor but also predict and enhance various aspects of production.
Key Applications of GlobalReader’s Machine Learning:
Proactive Problem-Solving: Unlike traditional monitoring systems, GlobalReader’s machine learning tools actively predict potential equipment issues before they occur. This proactive approach enables manufacturers to address problems early, reducing downtime and avoiding costly disruptions.
Adaptive Learning: GlobalReader’s machine learning algorithms continuously learn from the data they analyse, becoming more accurate over time. This adaptive capability means the system gets better at predicting maintenance needs and optimising production settings, helping manufacturers stay ahead of potential challenges.
Optimised Resource Allocation: Machine learning helps manufacturers make the most of their resources by analysing data to identify the most efficient production strategies. This includes adjusting schedules, fine-tuning machine operations, and managing energy use to reduce waste and improve overall efficiency.
By integrating machine learning in manufacturing through GlobalReader’s solutions, manufacturers gain a powerful tool for enhancing productivity and maintaining high-quality standards. The ability to predict, adapt, and optimise based on real-time data allows companies to transform their shop floors into dynamic, intelligent environments that are prepared for the challenges of modern manufacturing. Here’s how you can effectively implement machine learning technologies and overcome common challenges.
Steps to Implement Machine Learning on the Shop Floor:
Assess Your Current Systems:
Start by evaluating your existing equipment and data capabilities. Identify which areas of your production process could benefit most from machine learning, such as predictive maintenance or quality control.Choose the Right Tools:
Invest in machine learning solutions, like those offered by GlobalReader, that align with your specific manufacturing needs. Ensure the tools you choose can integrate seamlessly with your current systems and provide real-time data analysis.Train Your Team:
Provide comprehensive training for your staff on how to use machine learning tools effectively. This includes understanding how to interpret data insights and apply them to optimise production processes.Monitor and Optimise:
Regularly review the data and insights generated by your machine learning tools. Use this information to fine-tune operations, improve efficiency, and adapt to any changes in production needs.
Overcome Challenges - Do the Culture Change:
One of the biggest challenges our customers have concerns really the way work and processes have been done and based on the data, how they should be done. This is really a massive change in the culture of the company.
Implementing a culture change in a factory, especially when introducing new technologies like sensors and production tracking systems, can be challenging. Resistance often arises from both the workforce and management. Workers might feel threatened by technology, thinking, "No sensor is telling me how to do my job!" On the management side, there can be hesitancy to disrupt existing processes. So, how can these situations be handled effectively while ensuring the new way of working is embraced?
1. Acknowledge Concerns, Don't Dismiss Them
The first step is to recognise and address the concerns of both workers and managers. It’s essential to understand that resistance is often driven by fear—fear of the unknown or fear of losing control. Instead of simply dismissing concerns, open up the conversation.
Hold meetings where workers can express their worries, and management can explain the why behind the change. Make it clear that the goal isn’t to replace human expertise but to enhance it. By acknowledging their experience, you show respect for their work.
2. Communicate the Benefits Clearly
The message shouldn’t be, "You’re doing your job wrong," but rather, "We’re working together to improve efficiency." Explain how the new systems, like sensors and real-time data, will make everyone's jobs easier and less stressful. Highlight that these tools can reduce downtime, prevent breakdowns, and allow workers to focus on higher-value tasks instead of firefighting problems.
Present examples of how other companies have successfully improved efficiency and reduced workload by embracing technology. Frame it as a team effort to make the entire operation smoother and more rewarding for everyone.
3. Engage Employees Early and Often
Involve workers in the process from the start. Let them be part of testing new technologies and provide feedback. When employees see that their input is valued and that they have a say in how things are implemented, they’re more likely to support the change.
Consider running pilot programs where small teams can test the new systems, such as GlobalReader's sensors or Planner tool. This gives them hands-on experience and helps shift their perspective from viewing technology as a threat to seeing it as a tool for empowerment.
4. Provide Training and Support
Workers and managers need to feel confident using the new systems. Offer thorough, ongoing training to ensure that everyone understands how the technology works and how it benefits them personally.
Make training sessions hands-on and collaborative. Instead of just focusing on how the system works, relate it to everyday tasks and show how it can solve problems they’ve faced in the past. For example, how predictive maintenance can reduce unplanned machine breakdowns, giving workers more control over their schedules.
5. Frame It as a Long-Term Partnership
The goal should be to establish a partnership between workers, management, and the technology itself. Sensors and real-time data aren’t there to replace decision-making but to provide insights that can lead to better outcomes. The GlobalReader tools, for instance, offer transparency and help identify areas where improvements can be made without adding extra stress.
Use phrases like "We’re empowering you with the tools to make better decisions" or "This technology is an extension of your expertise." Emphasise that it’s a continuous process of improvement, not a one-time change.
6. Celebrate Early Wins
As the new systems start showing results—whether it’s reduced downtime, better resource allocation, or improved workflow—celebrate these wins with the entire team. Recognition helps reinforce the value of the changes and encourages ongoing support.
Share success stories within the company, highlight measurable improvements, and recognise individuals or teams that have adapted well to the new systems. Make everyone feel that they are part of the factory’s success.
7. Cultivate a Continuous Improvement Mindset
Finally, foster a culture of continuous improvement. Encourage feedback, make adjustments based on what the workers and managers are experiencing, and stay flexible. This reinforces that the change is a journey, not a one-time shift.
Hold regular check-ins and workshops where employees can discuss what’s working and what isn’t. This will help maintain momentum and ensure that the technology becomes a valued part of daily operations.
Benefits of a Smart Factory level by level:
Value for CEO
Smart Factory technologies provide CEOs with clear visibility into production trends, helping them make data-driven strategic decisions that align with long-term business goals. The integration of real-time data ensures CEOs can foresee opportunities for growth and innovation while staying ahead of the competition.
Value for HR
HR gains powerful tools for people management, ensuring that the workforce is organised and aligned with production goals. With people recognition systems in place, employees’ achievements are highlighted, boosting morale, while training programs can be efficiently tailored to upskill teams and improve performance.
Value for CFO
For CFOs, a Smart Factory delivers accurate production costs by providing precise, real-time data on resources and operations. Digital data exchange streamlines financial reporting and helps in generating bonus reports that are directly linked to performance metrics, making financial planning and forecasting more reliable.
Value for Technical Manager
The Smart Factory eliminates the need for reactive problem-solving, as predictive maintenance ensures equipment runs smoothly. This means the Technical Manager can finally stop “firefighting” breakdowns and focus on long-term improvements, leading to a more stable production environment.
As you see, not easy. But do you think the benefits outweigh the reason not to take the 5 steps of digitalisation through? We say they definitely do! Want to become a fully digitalised manufacturer? Boost efficiency? Increase revenue? Finally achieve your goals? Contact our Sales team and schedule a meeting.