Synchronous
Zeno

INTRODUCING THE MANUFACTURING DECISION PLATFORM

Tomorrow’s winners in manufacturing must evolve from systems of record such as ERP, MES, gantt, and spreadsheet tools to systems of intelligence. We imagine a future where factories always know the latest conditions and execute near optimal decisions at all times.

Synchronous Zeno is the culmination of our early work to provide manufacturers with an exponential jump in productivity. With synchronized data and decisions generated and updated in real-time, Synchronous Zeno provides a unified platform for effective cross-departmental collaboration and better decision making to happen. Below are the core technologies and technical breakthroughs which make this new paradigm possible.

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FLEXIBLE GRAPH DATA STRUCTURES
Making production decisions requires intimate knowledge of the constraints, dependencies, rules, and objectives governing factory operations. The criticality of this information revolves around their relationships between each other. We quickly realized that traditional table-based databases and off the shelf graph databases were insufficient for the varied complexity in manufacturing. We custom built our own graph data structures and database, capable of representing a wide range of these relationships with ease. This enables us to capture and handle the operational nuances across thousands of factories, irrespective of vertical or use case.
TRACKING OF TIME AND REVISIONS
Generating and updating decisions on production plans and schedules requires a system capable of handling the past, present, and future. Furthermore, new and revised information will be flowing into the system from the factory floor and across departments. We took our graph database one step further by building time dependency handling, data synchronization, and data revisions directly into the data structures. Unlike traditional databases and data structures, we view data less as static objects in fixed periods of time, and more as dynamic entities coming in via data streams with a conceptualization of time.
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TRACKING OF TIME AND REVISIONS
Generating and updating decisions on production plans and schedules requires a system capable of handling the past, present, and future. Furthermore, new and revised information will be flowing into the system from the factory floor and across departments. We took our graph database one step further by building time dependency handling, data synchronization, and data revisions directly into the data structures. Unlike traditional databases and data structures, we view data less as static objects in fixed periods of time, and more as dynamic entities coming in via data streams with a conceptualization of time.
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PERFORMANT SCHEDULING AND PLANNING ALGORITHMS
To surface near optimal decisions and construct them into a production plan and schedule requires the ability to simultaneously consider a variety of constraints, rules, and variables while balancing optimization over multiple objectives. We needed something more than operations research optimizers, so we pulled concepts from spectral graph theory and lie algebra to build generalized, high performance algorithms, which work in tandem with our custom graph data structures and database, to unlock new possibilities in real-time decision making in complex manufacturing environments.