Over the past decade, the manufacturing industry has seen remarkable advancements. Smart factory systems, powered by cutting-edge technologies like machine sensors and artificial intelligence (AI), are becoming the heart of modern production facilities.
These technologies have the potential to significantly boost productivity and generate vast amounts of valuable data, which, when harnessed effectively, can inform decision-making at every stage of the production process. According to a recent study from Deloitte, technology is poised to play a significant role in supporting manufacturers in taking on the challenges they could face this year.
Most recently, it was reported at the SEMICON WEST event from the CEO of SEMI that artificial intelligence is contributing largely to the growth of the industry; it is predicted that by 2030, semiconductor manufacturing will be a $1 trillion industry.
The data produced by sensors and edge computing systems provide valuable insights, allowing manufacturers to streamline operations and proactively manage their systems.
However, leveraging the potential of these advanced systems requires more than just collecting data; it requires tools capable of transforming that data into actionable insights. While many manufacturers have specialized tools, these often have limitations, including complexity, scalability issues, and lack of adaptability, which restrict their use and hinder full data utilization.
Let’s explore how manufacturers can address these challenges by embracing the visual data science approach. This approach not only democratizes data analysis for all engineers but also combines the best of the available tools for analysing data. Once again the goal is to increase productivity, efficiency, and yield across the entire manufacturing process—by reducing time to insights in a way that isn’t possible with traditional tools.
The challenge of data in manufacturing
The huge amount of data generated by modern manufacturing systems poses significant challenges. For example, semiconductor manufacturers can produce dozens of petabytes of data annually, encompassing everything from metrology data, electrical tests data, sort data, reliability data, and more. Analysing such massive data sets can overwhelm manufacturers, making it difficult to prioritize the most relevant data for actionable insights.
Another challenge is ensuring the data is trustworthy. Data cleaning can consume up to 80% of analysts’ time, delaying the discovery of cost-saving and efficiency-boosting insights.
Additionally, multiple data sources remain a hurdle. With data often scattered across various systems—both at rest and in motion—combining and analysing these disparate sources can be daunting. On-site data processing also becomes increasingly complex as data volumes grow, often requiring advanced hardware, software, or outsourcing to machines able to handle the computational load. For optimal performance, manufacturers need flexible and scalable solutions that allow prompt analytics and computational flexibility.
Collaboration across teams is another challenge. Many data tools are accessible primarily to data scientists, leaving technical and non-technical stakeholders on the periphery. This lack of collaboration slows down the pace at which new insights can be gained and limits buy-in from other departments, preventing scalable innovation.
Unlocking manufacturing potential with visual data science
Traditional data tools often silo data manipulation and visualization, which is insufficient in today’s interconnected manufacturing environments. To truly leverage data, manufacturers need a more integrated approach, and visual data science provides just that.
Visual data science allows users, from engineers to executives, to transform raw data into intuitive visual representations, enabling easier analysis and faster decision-making. This democratizes access to insights, ensuring that anyone in the organization can contribute to process improvements.
An example of a powerful visual data science tool is Spotfire, which provides a platform for data manipulation, analysis, and visualization. Users can prepare and explore their data within a single environment, eliminating the need for multiple tools. Spotfire “self-service” analytics software makes it accessible to users at all levels, reducing dependence on specialized statisticians and creating a culture of data-driven decision-making across the organization.
Spotfire also offers customizable features, by letting experts enhance Spotfire by creating reusable data functions that can perform pretty much any type of calculation. These functions can be shared with non-experts, ensuring that anyone in the company can apply the most relevant analyses to their work.
Manufacturers have often the need for specialized visualizations. For example, in the semiconductor industry, wafer maps need to be overlaid, binned, and analyzed to quickly understand quality issues—often concentrated in specific areas. Spotfire offers Mods which are innovative “grab and go” custom visualizations that leverage the power of Spotfire to extend the analytics experience. The Mods framework makes it easy for anyone to build, share, and use any new type of visualization like the Violin Plot Mod used to compare yield of manufacturing processes, machines, or batches.
Real-world success: Hemlock Semiconductor
Hemlock Semiconductor faced challenges in analysing product quality, lowering costs, and optimizing energy consumption. Their data was siloed, making it difficult to analyze anomalies and optimize production. With Spotfire® Visual Data Science, Hemlock Semiconductor has been able to “see” data, address new markets based on product quality, and improve their overall process management. The platform also helped the company optimize energy use, saving $300,000 per month.
Data-driven innovation at Brembo
Brembo, a world-leading manufacturer of high-performance brake systems, sought to evolve its analytics infrastructure and improve process efficiency. With Spotfire, Brembo gained detailed insights into operations, improved predictive maintenance, and enhanced product quality. Spotfire visualizations allowed Brembo to share insights across teams, boosting collaboration and production efficiency, resulting in a 25% increase in revenue.
Future-proofing manufacturing with visual analytics
Visual data science is revolutionizing manufacturing by transforming complex data into clear, actionable insights. By adopting tools like Spotfire, manufacturers can shift from reactive to proactive process management, improving efficiency, productivity, and decision-making across all areas of operation.
As more companies embrace visual data science, they are better equipped to stay competitive in an increasingly data-driven world. Spotfire, with its advanced analytics capabilities, is helping manufacturers worldwide harness data insights to drive innovation across their operations.
Alessandro Chimera, Sr. Principal Industry Analytics, Spotfire
Alessandro is a key member of the Vertical GTM Strategy team, where he delivers expert insights and guidance across the enterprise. Specializing in advanced analytics, Alessandro addresses the most complex challenges in the Manufacturing and Energy sectors, offering deep dives into technical solutions and the latest market trends. He is a sought-after speaker at industry events, a frequent webinar host, and a contributor to the Spotfire blog. With a passion for data, Alessandro holds a degree in Computer Science and has a background in Electronic Engineering. Fluent in Italian, English, and German, Alessandro brings a global perspective to his work.
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