Powerful visualizations for operations management

The latest release of ABB Ability™ Knowledge Manager (KM) introduces five powerful chart widgets - Waterfall, Jack-Knife, Scatter, Heatmap, and Correction Tracking - designed to help cement, mining, metals, and other industries get more out of their process and production data. This article explains how to apply each chart effectively and the benefits you can expect.

ABB Ability™ Knowledge Manager is an industrial operations management software that helps connect data from any source, understand it through analysis, and act on insights. Whether the goal is to reduce production variability and energy consumption, prevent unplanned downtime, or improve laboratory accuracy in quality control workflows, these new visualizations will help users reveal specific patterns, relationships, and anomalies that traditional charts might miss.

Chart type summary

Chart

Best for

Question to answer

Key benefit

Waterfall

Production / energy analysis

How did we get this result?

Track cumulative costs

Jack-Knife

Maintenance prioritization

What should we fix first?

Focus on biggest problems

Scatter

Process optimization

How do these variables relate?

Find optimal parameters

Heatmap

Pattern recognition

When do problems occur?

Spot time-based issues

Correction Tracking

Compliance & audit

What changed and why?

Complete data integrity

*This article highlights the five newly added chart types in the latest release. ABB Ability™ Knowledge Manager also includes a comprehensive library of standard chart types: Area, Bar, Bullet, Cluster, Donut, Histogram, Gauge, Line, Pareto, Pie, and Spider charts.

1. Waterfall Chart

The Waterfall chart visualizes sequential values with intermediate sums, showing how individual components contribute to a cumulative total. Think of it as a visual profit-and-loss statement for your operations. It is perfect for production analysis, energy consumption tracking, and understanding how multiple factors combine to create final outcomes. It answers the question: "How did we get from point A to point B?"

Application example in pellet production
By visualizing cumulative production losses across the pellet plant process chain, the waterfall chart identified crushing and screening as the primary bottleneck causing the production shortfall - leading to targeted improvements to recover capacity".

Waterfall

Business benefits

  • Financial transparency: Instantly see which factors drive profitability
  • Energy analysis: Track where energy is consumed or recovered in your process
  • Cost breakdown: Identify the biggest contributors to operational costs
  • Budget variance: Compare planned vs. actual values across categories

 


2. Jack-Knife Chart

The Jack-Knife chart plots event frequency (x-axis) against average event duration (y-axis) on a logarithmic scale, creating a powerful prioritization matrix for maintenance and reliability teams. Designed specifically for downtime analysis, this chart helps maintenance teams answer: "Which problems should we fix first?" It separates chronic issues (frequent but short) from acute problems (rare but lengthy).

Example Interpretation: A dot in the upper right showing "Conveyor Belt Alignment" with 20 stops averaging 2.5 hours each represents 50 hours of lost production is your top priority for improvement.

Application example in mining
A mining operation identified that "Crusher Jaw Adjustment" appeared in the Chronic zone with 45 stops per month. By implementing automated adjustment, they reduced stops by 80%.

Jack Knife chart

Business benefits

  • Data-driven prioritization: Focus resources on problems with the biggest impact
  • Maintenance optimization: Distinguish between preventive and predictive maintenance needs
  • ROI justification: Quantify the business case for equipment upgrades
  • Reliability improvement: Systematically eliminate chronic and acute issues

3. Scatter Chart

A scatter chart plots two variables against each other, with each data point representing a specific observation. It reveals correlations, clusters, and outliers that might indicate cause-and-effect relationships.

It is essential for correlation analysis, quality control, and process optimization. It answers: "How do these two variables relate to each other?"

Advanced Features: Embedded Ellipse

Embedding an ellipse to a scatter chart transforms it from a simple data plot into a powerful Statistical Process Control (SPC) tool.

  • Defining the "Normal" Operating Zone: The ellipse acts as a visual boundary for "Standard Operating Conditions." If 95% of your high-quality production runs fall inside the ellipse, any point appearing outside it is an immediate signal of a process deviation.
  • Early Detection of Outliers: In a crowded chart with thousands of data points, it is hard to spot a single bad batch. An ellipse makes outliers "pop" visually, allowing for faster root-cause analysis (e.g., "Why was the kiln oxygen so high for this specific clinker batch?").
Scatter Chart

Application examples in cement production

  • Kiln Performance vs. Fuel Mix: Analyze how the percentage of Alternative Fuels (e.g., biomass or RDF) affects the Kiln Hood Temperature. This helps operators find the "sweet spot" where fuel costs are minimized without sacrificing clinker quality.
  • Cement Fineness vs. Compressive Strength: Plot the Blaine value (fineness) against the 28-day strength results. This allows quality managers to optimize grinding energy; if increasing fineness beyond a certain point doesn't improve strength, they can reduce mill power.
  • SO3 Content vs. Setting Time: Monitor the chemical balance of the cement. A scatter plot can reveal if high sulfur levels from fuel are causing erratic setting times in the final product.
  • Power Consumption vs. Feed Rate: Identify the efficiency curve of a Vertical Roller Mill (VRM). You can see at what feed rate the energy consumption per ton ($kWh/t$) is lowest.

Business benefits

  • Process optimization: Identify optimal parameter combinations
  • Quality prediction: Predict product quality from process variables
  • Energy efficiency: Find the sweet spot between throughput and energy consumption
  • Root cause analysis: Discover which variables actually influence outcomes

4. Heatmap

A heatmap uses color intensity to represent data values in a grid format, making it easy to spot patterns, trends, and anomalies across time periods and multiple variables simultaneously. It is perfect for identifying time-based patterns, comparing multiple signals, and spotting anomalies in large datasets. It answers: "When and where do problems occur?"

Application example in pulp production
A heatmap showing bleaching chemical consumption spikes every Monday morning and after maintenance shutdowns, reveals startup procedure inconsistencies that, once standardized, can reduce costs.

Heat map

Business benefits

  • Pattern recognition: Instantly spot daily, weekly, or seasonal patterns
  • Anomaly detection: Unusual colors highlight problems immediately
  • Capacity planning: Identify peak usage times for resource allocation
  • Multi-variable comparison: Monitor dozens of signals simultaneously

5. Correction Tracking Chart

The Correction Tracking Tool is a specialized widget that visualizes all data corrections and configuration changes made to logs and their dependencies over time, ensuring complete audit trails and data governance. It is critical for quality management and maintaining data integrity. It answers: "What changed, when, and why?"

Application example across industries
A customer uses Correction Tracking to maintain compliance. When an auditor questioned a record, they instantly provided a complete audit trail showing all corrections, approvals, and justifications, passing the inspection without findings.

Business benefits

  • Regulatory compliance: Complete audit trail for industry regulations
  • Data quality: Track and validate all manual corrections
  • Troubleshooting: Understand if problems stem from data or configuration changes
  • Accountability: Know who changed what and when
  • Impact analysis: See how changes propagate through dependent calculations

Putting it all together: a comprehensive analysis workflow

  • Step 1: Identify patterns (Heatmap) - Use heatmaps to spot when and where problems occur across your operation.
  • Step 2: Prioritize issues (Jack-Knife) - Plot downtime events to determine which problems have the biggest impact.
  • Step 3: Find root causes (Scatter) - Correlate process variables to identify what's driving the problems.
  • Step 4: Quantify impact (Waterfall) - Calculate the financial or energy impact of the issue.
  • Step 5: Verify data quality (Correction Tracking) - Ensure your analysis is based on accurate, validated data.

With these five chart types within ABB Ability™ Knowledge Manager, you'll be equipped to see what others miss and act on what matters most. Use the form below to contact your ABB representative to activate the latest software release or to request a demo.

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