"Data and digitalization is a key to increased productivity," says Lydia Söderlund, Senior Consultant in Supply Chain & Production at Plantvision, who participates in a conversation about how digital technology and production data can transform today's manufacturing processes.
Why is data so important?
Production data is an invaluable asset for generating insights and making informed decisions. When collected and analysed, data can be used for a variety of purposes, from improving operational reliability to optimizing processes.
Lydia describes how data can be used for real-time monitoring and process optimization: "You can more quickly detect production stops and facilitate troubleshooting, or identify patterns that reveal inefficient processes. This leads to both increased productivity and greater transparency in operations."
Andreas Eriksson, also a Senior Consultant at Plantvision, emphasizes the importance of maintenance data: "By measuring parameters such as the power consumption of an electric motor, you can detect when a pump is wearing out and plan maintenance before a breakdown occurs. Predictive maintenance is a good example of how data can be used to minimize downtime."
How to collect production data?
Many machines in modern production environments already have sensors that track and log different types of data, but there may be a need to add additional sensors for specific measurements.
Lydia explains: "If you want to measure a specific parameter, such as the speed of a machine or the volume passing through a process, it may be necessary to install external sensors."
However, starting to collect data is not only about technology but also about strategy. A company should analyse its production maturity and consider which types of data are most important. If different systems are already in Location , integration may be needed to avoid so-called 'information islands' - where important information is scattered and difficult to access.
From information islands to a holistic view
A common problem in many production environments is that data is managed in separate systems, making it difficult to get a comprehensive picture.
Lydia describes how a client in the pharmaceutical industry struggled with this very issue:
"They had several different systems for planning, inventory and quality control, but lacked a centralized solution to aggregate the data. We helped them develop customized reports in Power BI that integrated data from multiple sources. This reduced their delivery-related delays to just 2% in one year."
The impact was so significant that other departments within the company wanted to implement similar solutions, creating a positive domino effect.
Digitalization as the key to AI and future technologies
digitalize production is not just a matter of increasing efficiency - it's a prerequisite for harnessing future technologies, such as artificial intelligence (AI).
Andreas points out: "To benefit from AI, you first need access to relevant and structured data. AI can then be used to improve everything from production planning to quality control."
Digitization also creates a platform for continuous development, where data can be visualized and analysed in real time, leading to faster and better decisions.
Final words: Small steps towards big results
When it comes to implementing data-driven solutions, Lydia recommends starting small: "Identify a department or process where digitization can bring clear results, and build from there. Success in one part of the business often creates inspiration for others."
With production data as a driver, industry can not only increase its efficiency but also secure its competitiveness in an increasingly data-driven world. As Andreas summarizes: "Data is not just a resource - it is a key to the future."
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