Manufacturing Machine Learning & AI Solutions

Mosaic has deployed AI, ML, and advanced analytics for the following manufacturing use cases

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Supply Chain Optimization

Mosaic helps manufacturers adopt automation & insights as key heuristics in the process of keeping product in stock and planning for demand.

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Predictive Resource Planning & Allocation

Mosaic uses machine learning to make sense of unstructured/structured data to automate & improve resource allocation.

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ML-Predictive Maintenance & Line Optimization

Our clients leverage Mosaic’s expertise in data science to achieve true PdM, decreasing downtime, and cutting costs.

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Deep Learning Informing Quality Management

Mosaic deploys custom AI systems that utilize advanced ML techniques to automate defect detection.

logos including Leibherr , Cat, Hasbro, and Boeing

Mosaic has compiled our industry expertise into a Machine Learning playbook for Manufacturing.

Produce more, higher-quality products at minimum cost with AI and machine learning

Manufacturing holds multiple predictive analytics and data science opportunities. With the rise of the Internet of Things (IoT) and data collection technologies becoming more accessible, manufacturing companies have a wealth of data to mine. Companies can use machine learning and AI algorithms on these data sets to apply data-driven guidance and decision making to improve efficiency and quality, and to reduce costs.

Manufacturers can run Proof of Concept (PoC) projects to prove value and garner larger investment before spending multiple millions of dollars on an analytic infrastructure. Many companies turn to a consulting firm like Mosaic to help them in developing a quick-win plan and executing on that plan.

The days when a small group of executives would make million-dollar decisions behind closed doors are over. There is simply too much data for leaders to make sense of. Businesses that combine executive expertise and predictive manufacturing analytics are seeing an increased competitive advantage, along with a substantial boost to the bottom line.

Mosaic’s manufacturing customers are a perfect fit for AI & ML improvements. Despite the 4.0 revolution still being in early stages, we are already deploying significant AI-driven benefits. From the design process, to the line operations, to supply chain, and administration, AI supports the way firms produce products and process materials. 

Don’t see your specific problem? Drop us a line to see if we have worked on something similar.

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Manufacturing Success Stories

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Combatting Supply Chain Disruptions with Data Science

Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain. Companies who have deployed data science into their businesses will be poised to automate AI-driven decisions to even very sudden disruptions. 

Predictive Maintenance Modeling for Industrial Machinery

Mosaic was contracted by multi-national manufacturer of construction and mining equipment to develop a proof-of-concept predictive maintenance model to predict equipment failure before it happens to minimize downtime and optimize maintenance schedules.

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Advanced Revenue Forecasting

This manufacturer wanted to segment their forecasts by the different markets that they serve, e.g., aerospace, consumer electronics, and life sciences. The company had been collecting transactional data by line of business, region, and industry. Now that the company had collected all this data, they needed to perform ML analysis on it to extract value. With no internal data scientists available for this work, Mosaic was tapped.

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Inventory Management Analytics

Advanced analytical techniques help manufacturers reduce inventory levels of parts required in manufacturing activities while maintaining confidence that they will not run out of parts. Mosaic was tapped to help a manufacturing company in the semiconductor industry develop an inventory management analytics system.

“In order to stay competitive and offer a superior customer experience, Manufacturers need to embrace data science and the shift towards data driven decision making.”

Chris Brinton, CEO, Mosaic Data Science
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