With the adoption of methodologies such as lean manufacturing and Six Sigma, as well as the increasing use of automation technologies, manufacturers have aimed to optimize resources and productivity and eliminate waste in manufacturing. Yet variability is still inevitable, even more so as products and their production become more complex and involve many different factors throughout the manufacturing process. Variability can cause bottlenecks and poor quality output, and can also lead to poor capacity management and substantial financial losses.
It’s not enough for a manufacturer to analyze weekly or daily reports of resources, production capacity, and orders. With the complexity of production and the volatility of customer demand, manufacturers must achieve real-time awareness and control. Operation leads must stay apprised in realtime of potential variability that could disrupt the supply chain, threaten product quality, or even suggest theft or other supply chain integrity issues, ultimately putting customer relationships at risk.
The ability for manufacturers to leverage “Big Data” to create comprehensive, meaningful, real-time intelligence is the key to substantial business benefits, including identifying where variability might impact yield and facilitate process improvement. Of course, leveraging this data to get to these kinds of definitive, real-time insights is no easy task, with the systems, technologies and processes used in a complex manufacturing organization. A single manufacturer may be tracking operations and resources with many different types of data — machine logs and feedback, multiple sensors and RFID technology, enterprise data warehouses, text messages and emails, and even spreadsheets, to name a few. These types of data represent both static and dynamic data; all of which are typically locked inside disparate systems.
Striim ties multiple data sources from across a manufacturer’s departments, machines, systems, and sensors together into a single platform with ease. With pre-built data adapters, data correlation from multiple streaming data sources happens in real time—log files, sensor data, machine feedback, historical data from databases, social feeds, and more.
The platform leverages historical static data to inform norms and context, while using streaming data to identify anomalies in real time. For example, the Striim platform helps manufacturers monitor production flows by calculating expected manufacturing output in real time based on inputs — and can automatically alert companies when output is higher or lower than the original bill of materials specifies it should be within tolerance.
Business users then have the ability to correlate and aggregate pertinent data from across the business into a real-time view, applying business logic to all streaming and static data flowing through the Striim platform. This allows business analysts or operations leads to access analytics and reports regularly, and also to continuously query streams and react instantaneously when alerted to specific conditions that indicate variability that could put production in jeopardy then and trigger downstream workflows.
Striim is an end-to-end, enterprise-grade platform that allows IT professionals to focus on building out required business logic, rather than maintaining streaming data platform infrastructure. The platform offers robust services, high performance and enterprise scalability.
Manufacturers benefit from the Striim platform in the short term with, higher efficiency, lower waste, and reduced production costs. Over the long term, they can gain consistent product quality and higher output. In complex manufacturing environments, often there are dozens of fragmented processes and variables that impact output and costs. Our platform allows manufacturers to pull together data from across the organization into one place for real-time data correlation and analysis. This way, they can identify breakdowns and bottlenecks and determine whether inputs match outputs as expected. Data correlation also allows them to see how variability in one area might be impacting another and detect any troublesome patterns among departments, machines, processes or individuals. Companies can also establish business logic that alerts them to these patterns or bottlenecks as they happen. That means they address problems immediately before they affect the business.
The Striim platform is built for scalability and flexibility. Any micro application deployed can be opened in the Striim Flow Designer and reconfigured as the business process changes. Business logic is represented in a simple SQL-like language for easy use by a broad community of programmers.