Transform your manufacturing with data, from production to delivery

Accelerating the transformation to Industry 4.0

At Neal Analytics, we help manufacturers plan, build, and deliver their products and services more effectively by leveraging the power of the cloud, IoT data from field assets and the shop floor, and AI.

As equipment grows smarter, the data generated by these devices becomes a key driver for finding new productivity improvements opportunities. This (mostly IoT) data-driven transformation is one of the key components of what commonly referred to as Industry 4.0.

To take full advantage of these new and rich data sets, manufacturers need to first modernize the underlying data platform. Then, through advanced ML/AI models, new opportunities emerge to improve the end-to-end manufacturing value chain, from planning to end-customer delivery.

Neal’s custom-built solutions leverage the latest cloud, data, and AI platforms and technology to prepare your organization for the future, solve for your unique business challenges, and delight your customers.

Your manufacturing processes, transformed

We leverage our industry solution accelerators, cloud and data platforms expertise, and digital consulting services to help manufacturers accelerate their transformation journey to Industry 4.0, while minimizing risk and maximizing value.

Neal Analytics solutions are designed to support one, or several, of the following objectives:

Transform your workforce

Leverage business intelligence and advanced natural language understanding to put the right information in the hands of your employees at the right place and right time. Generate insights from data to empower your workers.

Build more agile factories

Modernize your data platforms and leverage AI to optimize your production lines, creating greater consistency, uptime and flexibility in the production process.

Create more resilient supply chains

Optimize your supply chain by building the right products at the right time through advanced forecasting and SKU assortment optimization. Optimize your distribution end-to-end with Edge computing, computer vision, and AI solutions.

Featured customer stories

Multi-National glass manufacturer: predictive maintenance for manufacturing equipment

Challenge Experiencing equipment failures unexpected costs in the production process. High machine downtime and low production availability Managers are challenged...
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High tech aerospace manufacturer: data infrastructure creation and pipeline automation

  Challenge A major manufacturer in the high-tech aerospace industry had developed a strong, lightweight carbon fiber-based airplane coating designed...
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Automotive part manufacturer: quality prediction and driver analysis for aluminum castings

Challenge The manufacturer has a population of parts which pass a final inspection but are actually defective The defective parts...
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Market leading craft brewery: scenario identification and prioritization

Challenge Brewery Management wanted to leverage analytics but was unsure where to begin Several potential use cases existed, but the...
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High Tech manufacturer: setup of EDW

Challenge High tech manufacturer had an on-going project to develop and deploy a large EDW with accompanying ETL processes in...
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Our solutions

Data estate modernization

Data estate modernization

To reap the benefits that Industry 4.0 promises, data sources across equipment, production lines, and plants need to be collected and stored. To achieve this, manufacturers need to evolve their data infrastructure into a modern cloud-based data estate.

A modern data platform, such as one built using Azure Synapse Analytics, enables dynamic scalability, increased security, and reduced IT expenses. It is the foundational element to a successful Industry 4.0 transformation. To be successful, a data estate modernization must bring together real time and historical data, market, production and supply chain data, as well as cloud, application and IoT data.

Neal Analytics can help manufacturers build the data estate for today, and set the foundation for the advanced analytics, ML, and AI workloads that will transform manufacturing efficiency and profitability.

Autonomous systems

Improving complex industrial production processes can provide outsized returns. Often, a few percent productivity increase can generate large bottom line returns. However, because of their complexity and the risks & costs associated with halting or slowing down a production line, fine tuning these process parameters often offers unacceptable risk/reward profiles.

Autonomous systems can help address this dilemma by leveraging AI to improve these processes.

Autonomous systems combine simulation and Deep Reinforcement Learning (DRL) to achieve new levels in equipment performance. Rather than programmed rules, these systems self-learn through trial and error.

The first step to reinforcement learning is to build a reliable simulator.  These simulators are designed to capture the intricacies of the environment.  From there, an AI agent is used to learn the optimal path based on a value function.


Predictive and prescriptive maintenance

Many businesses struggle to get the most value out of their manufacturing equipment or field assets. Maintenance programs designed to keep equipment up and running are often reactive, leading to unnecessary downtime and lost productivity when a problem occurs.

New advanced analytics tools have the potential to shift the dynamic and enable maintenance programs to be proactive. These tools empower organizations to take action before a production line shutdown or field equipment failure. It reduces downtime and its financial impact and increases return on assets.

Prescriptive maintenance goes a step further by providing insights related to the root cause of an issue through automatic detection. It enables maintenance crews to plan spare parts usage and equipment requirements for repairs before even visiting a site or customer. Prescriptive maintenance saves time and helps maintenance managers drive better outcomes.

Advanced demand forecasting

Unsold inventory heavily impacts the balance sheet. Manufacturing delays impact customer satisfaction and sales.

By forecasting demand more accurately and gaining insight into which factors are driving market demand, manufacturers can reduce both unsold inventory and delivery time.

Advanced demand forecasting from Neal Analytics helps provide a clear picture of where demand is heading, providing business decision-makers with the information they need to optimize operations and improve both top and bottom lines.

financial data analytics
man grocery shopping

SKU assortment optimization

Get the right product to market based on local customer needs, seasonality, and preferences with Neal’s SKU Assortment Optimization solution.

By analyzing historical sales data, combined with contextual data such as selling-point (stores or distributors) attributes, location-based data, you’ll gain machine learning-powered insights to personalize and optimize your product assortment for each outlet.

This personalization will be based on local needs, demographics, purchasing habits, local market idiosyncrasies, seasonality, and more.

IoT analytics

Sensors have the potential to provide clarity and visibility into the operations of a manufacturing organization.

However, to create value, sensor data must be connected and analyzed with the proper context.  It requires infrastructure planning, execution expertise, and advanced analytics knowhow.

IoT maunfacturing