White Papers

Powering The New Age of Manufacturing

How Sight Machine Delivers the Next Generation of Continuous Improvement

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Three Problems that Doom Digital Transformation Efforts — and How to Avoid Them

A Data-First Strategy Requires Changes in How Some Chemical Companies Operate

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Enabling ‘New Answers to New Questions’ via System-wide Data Visibility in the Paper and Tissue Industry

Breaking Down Silos and Building Insight for Paper and Tissue Manufacturers. Four Scenarios that ‘Make the Case’ for Sight Machine.

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Digital Manufacturing Data Readiness Audit

By providing a consistent methodology to assess data, manufacturers can establish a common vocabulary for describing the usability of data.

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Digital Manufacturing Lives on the Cloud

Manufacturers embarking on digital transformation projects face a series of early decisions that will ultimately determine if the projects succeed in transforming the company or become failed science experiments.

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7 Steps to a Successful Manufacturing Big Data Project

Manufacturers produce the largest volume, velocity, and variety of data. Manufacturing analytics hold the key to understanding. This paper provides a practical “how to” guide for launching a manufacturing analytics project. See how to avoid common roadblocks and pitfalls.

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Thought for Food: Breakthrough Analytics for Food and Beverage Manufacturers

How can you transform a huge repository of data into actionable intelligence and gain value from it?

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Advanced Insights: 5 Manufacturing Analytics Best Practices for Today’s Enterprise

With more intelligent use of factory data, today’s manufacturer is in a better competitive position. See how to achieve real-time visibility into your automation systems and manufacturing operations.

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Manufacturing Analytics: Uncover the Secrets on Your Factory Floor

For manufacturers, operational insight is masked by mountains of process and part data flowing from factory floor sensors, systems, suppliers, and other data sources. This paper makes the case for an advanced manufacturing analytics platform that helps uncover secrets from the factory floor for real-time, data-driven insight, enabling fact-based decisions.

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Case Study: Asian Paints

Asian Paints, India’s largest paint and coatings company, recently launched an initiative to harness its production data to drive business value. With Sight Machine’s help they achieved a 7% reduction in cycle time within 60 days of Sight Machine deployment.

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Is Your Company Ready for Digital Transformation?

Through our experience with dozens of companies embarking on digital transformation, Sight Machine has developed a standardized process to evaluate corporate readiness, identify appropriate projects — those most likely to succeed based on current readiness — and rank projects according to their readiness. We call this the Digital Readiness Index (DRI).

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JAPANESE

Manufacturing Performance Index (MPI)

In this white paper, we discuss a new productivity metric that lets manufacturers directly link productivity data to profitability. We believe this approach provides the flexibility and ease of use that manufacturers are looking for as they evaluate potential investments, including investments in digitization.

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Manufacturing Metrics in an IoT World: Measuring the Progress of the Industrial Internet of Things

This eBook demonstrates how Manufacturing Operations Management is still at the center of data collection, information handling, and operations management in most enterprises. The impact that IT trends are having on the Manufacturing Operations Management space are investigated, and suggestions are be given as to where thing will go in the coming years.

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Finding ROI in the Factory and Beyond: The Value of Industrial Big Data Analytics

We are in the midst of one of the most transformative periods in industrial operations and technology over the past 40 years. As industrial executives attempt to make sense of changing business models and technology landscapes, it is critical that a formalized and structured approach is taken.

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Sight Machine Enables Operational Intelligence with the Digital Twin

A key benefit of the digital enterprise is operational intelligence. A vast quantity of end-to-end manufacturing data is available in most plants and factories, but the question manufacturers often ask: How can we transform this huge repository of data into actionable intelligence to gain value from it?

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9 Ways Manufacturing Analytics Can Improve Your Profitability

Making Plant Data Continuously Useful for Operations, IT, and Data Science

With OEE Insight from Sight Machine, Metals Company Fixes 5% Scrap Rate.

High-speed, highly automated producer with outstanding production practices created real-time Data Foundation at multiple plants. New OEE gains achieved by detecting elusive bottlenecks and improving scrap.

High-speed, highly automated producer with outstanding production practices created real-time Data Foundation at multiple plants. New OEE gains achieved by detecting elusive bottlenecks and improving scrap.

World-class batch process manufacturer improved its throughput by 7% in only two months.

High-speed, highly automated producer with outstanding production practices created real-time Data Foundation at multiple plants. New OEE gains achieved by detecting elusive bottlenecks and improving scrap.

Global dairy processor optimized throughput and quality for a 5% increase in yield of its high-performance product line.

Insights within the first 2 weeks. Large paper manufacturer used Artificial Intelligence and Machine Learning to pinpoint discrepancies with Warp, defects and energy consumption.

Manufacturer of aerospace sensors performs root cause analysis with data to reduce quality problems across its 90 step-process.

Automotive manufacturer achieves 91% reduction in machine downtime through predictive downtime analytics.

World-class manufacturer, regularly recognized as a leader in quality and plant operations, reduces downtime, scrap and waste by deeply incorporating constant analysis of Data Foundation into its workflow.

Leading paper manufacturer improved energy use by analyzing thousands of data sources across all its processes.

Global manufacturer improved development and performance of supplier equipment by implementing a network of visibility and analysis tools across suppliers.

Leading contact lens manufacturer needed to analyze thousands of alarms on a highly automated line to identify throughput delays and reduce scrap.

One of the world’s largest medical device manufacturers struggled with CNC machines’ scrap rate.

Global automotive manufacturer produced engine blocks across 3 plants in its luxury division. Persistently high defects could not be resolved.

Major automotive supplier controlled costs and reduced waste in their seat production and assembly line.

Large pharmaceutical company wanted to take Continuous Improvement to the next level by reacting faster to losses in a new packaging line

Manufacturer analyzed CNC data to reduce downtime and variation

Leading hardware manufacturer enhanced its efficiency across multiple lines through automation and visualizing Takt time.

Heavy equipment manufacturer challenged by lack of visibility into downtime

Global brewer solves 20-year downtime problem by analyzing thousands of alarms per shift.