Achieve production goals, increase quality and customer satisfaction and lower energy costs with AI in manufacturing

Drive real-time interactions and automate digital decisions at scale. The more complex a manufacturing business becomes, the more it needs supporting technologies and increasingly digitized processes. Improve decisions and decision-making processes to make business decisions with greater objectivity as your business grows and expands. Make the most of your data with machine learning, gaining insights for company-wide decision makers that enable them to manage business complexity and unleash innovation.

The value of this solution:

• Trustworthy insights.
• Faster decision making.
• Reduced complexity.
• Accelerated innovation.

AI techniques used in this solution:

• Machine learning finds and visualizes stories and insights and also integrates model development and management capabilities.
• Intelligent decisioning enables you to achieve exceptional value across real-world use cases.

How AI helps:

• Improve decision quality and increase your competitive advantage by incorporating AI and machine learning models from a common repository in your preferred language.
• Make the best data-driven decisions when interacting with customers, partners, suppliers and employees.
• Easily create, manage and govern robust, analytically-driven business rules to power data-driven decisions at scale.
• Increase efficiencies, improving productivity and cost. Quickly execute the largest number of data-driven decisions and reduce the effort required to manage the environment.
• Easily test decisions before deployment to verify they deliver the expected results.
• Ensure your decisions are understood and trusted across the business with robust governance.
• Handle high data and decision volumes easily with a cloud-based architecture that can scale to meet your demands.
• Foster collaboration for users of all skill sets.

The AI models provide:

• Simulations that enable you to determine the outcome of different scenarios.
• Predictive analytics so you can solve issues before they happen.
• Self-service data preparation capabilities that access, profile, cleanse and transform data using an intuitive interface.
• Integrated model development and management capabilities – both SAS and open source.

Move from reactive to proactive maintenance and predict when parts will fail before there is an in-cab – or in-cabin – experience, improving the uptime of your customers' fleet. Significantly reduce diagnostic and repair time and minimize the costs of service disruptions by servicing connected vehicles more efficiently, accurately and proactively.

The value of this solution:

• Maximized uptime.
• Improved customer service.
• Cost savings.
• Greater efficiency.

AI techniques used in this solution:

• Machine learning finds and visualizes stories and insights that are easy to understand and explain.

How AI helps:

• Identify and prescribe actions to minimize unplanned costs, operations disruptions and safety hazards.
• Explore data, then interactively create and refine predictive models.
• Spot red flags hidden in torrents of fast-moving data.
• Easily build and adjust huge numbers of predictive models on the fly.
• Detect and diagnose issues faster to prescribe what actions to take.
• Improve reliability by forecasting remaining useful life to determine when something is likely to fail.
• Mitigate risk and predict future needs with a holistic view and optimized maintenance suggestions.
• Access, profile, cleanse and transform data using an intuitive interface that provides self-service data preparation capabilities with embedded AI.

The AI models provide:

• Detailed information about the fault and its severity.
• A recommended action plan.
• Building of predictive models from a visual or programming interface.
• The ability to connect, decipher, cleanse and understand streaming data.
• The ability to get started accessing and exploring data quickly and easily using the AI of Things (AIoT) sensor-focused data model.

Optimize processes, maintenance and productivity to achieve your production goals. Resolve issues faster by empowering employees to spend their time fixing problems instead of looking for them. Find the optimal balance of speed and quality to maximize profitability.

The value of this solution:

• Improved quality and yield.
• Maximized uptime.
• Faster issue resolution.

AI techniques used in this solution:

• Deep learning analyzes and optimizes production.
• Machine learning models evaluate the production process.
• Computer vision is applied to cameras used on production lines.

How AI helps:

• Analyze streaming data from diverse sources, uncover hidden insights and make real-time, intelligent decisions.
• Deploy models in minutes.
• Spot red flags hidden in torrents of fast-moving data.
• Optimization of product composition and production techniques.
• Quickly see and address inefficiencies across all assets.
• Identify potential issues with high-capital assets, such as aging and underperformance, so you can trust them and keep them running at maximum efficiency.
• Automatically detect problems so corrective action can be taken quickly.
• Calculate the next-best production process during an interruption to help avoid delays.

The AI models provide:

• Optimization techniques.
• Predictive maintenance at scale.
• Insights that enable you to unlock new levels of operational efficiency.
• Superior process optimization and quality.
• Automatic problem detection.
• Analysis of structured and non-structured data sources.

Decipher customer feedback from various sources. Customer feedback can come from a variety of sources, including surveys, call transcripts, emails and social media – and deciphering it can be difficult. Responses vary in intelligibility and can include statements about multiple items, making it challenging to identify the concern with a high degree of accuracy. SAS can help you understand customer feedback to uncover quality issues, implement innovative or necessary design changes, improve service efficiency, optimize repairs and improve customer satisfaction.

The value of this solution:

• Faster decision making and innovation.
• Greater productivity.
• Increased customer satisfaction.
• Cost savings.

AI techniques used in this solution:

• Natural language processing deciphers customer feedback from varying sources.

How AI helps:

• Understand what your customers are trying to tell you so you can put that information to work for your business.
• Improve customer satisfaction by responding to your customers' needs.
• Become aware of after-sale quality issues and implement corrective actions.
• Free up your employees to work on other important projects.
• Innovate faster by knowing what your customers want.
• Provide better service and optimal repairs that save you time and money.

The AI models provide:

The ability to decipher customer feedback so it can be used to make improvements across the business.

Identify unsafe behaviors to reduce accidents and unwanted events. Our enterprise-grade computer vision and sensor-enabled solution targets unsafe behaviors, eight of which appear on OSHA’s list of top 10 worker safety violations.

The value of this solution:

• Improved safety.
• Cost savings.
• Greater productivity.
• Regulatory compliance.

AI techniques used in this solution:

• Computer vision is applied to cameras to “see” unsafe behaviors as they happen.

How AI helps:

• Reduce and prevent safety incidents.
• Lower injury-related costs.
• Gain uninterrupted productivity and production for consistent yield.
• Comply with OSHA safety regulations.

The AI models provide:

• Automatic detection of unsafe behaviors in real time.
• Integration with the existing environment while maintaining compliance.

Enable newer employees to operate with greater expertise. Rapid skill turnover in manufacturing demands efficiency to manage high training costs and quick progress. LLMs create chatbots (copilots) using streaming data, manuals, SOPs and processes to upskill less experienced workers. These chatbots provide “how-to” instructions and guide the next-best action, helping employees make better, faster decisions.

The value of this solution:

• Cost savings.
• Faster issue resolution.
• Greater productivity.
• Quicker decision making.

AI techniques used in this solution:

• The LLM acts as an advanced search engine, retrieving information from an internal database and assembling the information in a relevant and consumable manner.
• SAS Intelligent Decisioning provides corrective action with a feedback loop.

How AI helps:

• Retain skills and knowledge turnover, reducing training expenses.
• Accelerate onboarding and quickly upskill newer employees, keeping the business running smoothly.
• Make the right decisions as events occur, avoiding costly mistakes.

The AI models provide:

• Simplified code compilation – employees can prompt code to get the analytics setup they need faster.
• Automated code-commenting capabilities.
• Streamlined translation of user prompts into machine-readable code.
• Easy interaction with analytics using natural written language.

Use LLMs to create chatbots (copilots) that help mathematically optimize warehouse space. Your warehouse specialists and logistics operators can confidently make decisions with speed and precision.

The value of this solution:

• Faster decision making.
• Better outcomes.
• Maximized operational efficiency.
• Supply chain management.

AI techniques used in this solution:

• The LLM acts as an advanced search engine, retrieving information from an internal database and assembling the information in a relevant and consumable manner.
• Optimization considers more alternative actions and scenarios and determines the best allocation of resources and plans for accomplishing goals.

How AI helps:

• Eliminates hallucinations for trustworthy decisions you can be confident in.
• Faster and more accurate results with the reduction of manual data assessment.
• Mathematically solves the warehouse space optimization, eliminating the need for spreadsheet estimation.
• Easy interaction with analytics using natural written language.
• Both technical and non-technical users can intuitively use the AI-based assistant.

The AI models provide:

• Confident decision making by integrating GenAI models into decisioning workflows, business processes, AI and machine learning applications and data.
• Direct understanding of why inventory diversion and repatriation recommendations were made.
• Time-saving, accurate results with the reduction of manual data assessment.
• Elimination of the need for spreadsheet estimation.
• Built-in integration with SAS Visual Analytics or Power BI that enables workers to view real-time information, run multiple scenarios and compare results.
• Event planning and scenario analysis.
• The ability to quickly determine the impact of change in forecasted demand or set target warehouse utilization.

Generate synthetic data to cost-effectively fill in data gaps and protect sensitive or proprietary data, improving the usefulness of the data set. With more complete data sets, you can test and refine assembly processes, provide quality data for training and evaluating machine learning models, and support process improvement and optimization.

The value of this solution:

• Cost savings.
• Production optimization.
• Improved quality and yield.
• Increased customer satisfaction.

AI techniques used in this solution:

• Synthetic data fills in data gaps and protects existing data.

How AI helps:

• Save money on the high costs of data collection.
• Generate more complete data that can improve the usefulness of the data set.
• Improve quality for higher yield and increased customer satisfaction.
• Optimize production processes for greater efficiency and productivity.
• Safeguard sensitive manufacturing or customer data.

The AI models provide:

• Trustworthy, simplified data augmentation and generation.
• Better protection of customer, proprietary or other sensitive data.
• More accurate and useful insights.