Introduction

The chemical industry is one of the cornerstones of many end-market industries such as agriculture, automotive, electronics, and construction. It converts raw materials such as air, water, oil, and natural gas into intermediates, which in turn are transformed into products we use every day. Given its fundamental role and importance to end-market industries, it’s understandable that this industry is very risk-averse. As a result, innovation hasn’t been as prominent as in other industries, but recently that seems to be changing as breakthroughs in hardware and software technology are bringing significant benefits to the industry.

Call it digital transformation, Industry 4.0, or smart manufacturing, it’s inevitable to notice that the chemical industry is evolving digitally, reflected in even more connected and precise business and resource management systems and processes. And when we talk about networked or highly interconnected data, we enter the world of network analysis, graph models, and graph algorithms, where Memgraph is one of the frontrunners and one of the most important developer tools. But before we talk about how Memgraph can help you, let’s first mention a few use cases for chemical graphs.

Applying graphs in chemical - Graph applications and their value

Real-time process optimization (RTO) with graphs

• The central issue in RTO use is the generation of accurate process models reflecting current operating conditions. It can take hours, days, or even weeks, depending on the complexity of the process network, and is costing chemical companies millions in productivity & profitability losses. With graphs models and algorithms you can compute missing state parameters and handle process networks with thousands of unit operations, equations, and constraints reducing maintenance costs and giving everyone across the organization access to on-demand updated process models for research, planning, and debottlenecking activities.

Graphs as a solution for supply chain scheduling problems

• Graph patterns are obvious in the plant data and its scheduling logic. Some products have a list of sub-products they depend on in order to be produced. The instructions for mixing ingredient products into a resolving product, also called recipes, are not unique, as sometimes multiple of them can construct the same product. This is a perfect scenario to combine graph modeling and analytics with optimization algorithms.

Create chemical digital twins with graph as a system integrator

• Digital twins enable plant management to evaluate the impact of adjustments in the production process and to develop and deploy advanced process control systems. But one of the problems with digital twins is that you need to integrate data from various flowsheet models, P&IDs, data historians, and ERP systems along with complex business logic rules. This is not an easy task and graph platforms like Memgraph can be considered one of the top solutions. Plus, when you take into consideration that alongside the integration of various data sources, graph helps you to develop advanced real-time optimization, data reconciliation, and simulation algorithms there is a case to use graph technology for these types of problems.

Why Memgraph?

Integrate and process historical and real-time data

Memgraph connects directly to your streaming and historical data infrastructure so you and your team don’t have to spend countless hours building and maintaining complex data pipelines. Ingest data from sources like Apache Kafka, RedPanda, or Apache Pulsar as well as SQL, CSV, and JSON and keep your data in sync through your source with continuous data ingestions.

Map complex data intuitively and extend your data model

Memgraph uses the property graph data model, which stores data in terms of objects, their attributes, and the relationships that connect them. This allows developers to intuitively represent complex data problems without having to worry about JOIN operations or other complex constructs. Also, it enables easy maintenance, change, and expanding of the data model without spending days rethinking it.

Engineered with fast performance and resilience in mind

Memgraph is lightning fast and delivers high performance for both transactional and analytical queries even in highly concurrent environments. At the same time, Memgraph ensures your data is both correct and safe with automatic snapshot and write-ahead logging, fully supported with ACID transactions.

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