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Manufacturing Execution System

Whitepaper

Manufacturing Execution System

A digital transformation roadmap, considering the technological requirements, interdependencies and constraints, as well as linkages to business challenges and goals will help organizations maximize return on their investments. While an ERP system along with an SRM and CRM helps horizontal integration of the value chain, an MES helps largely in the vertical integration of an organization. The white paper gives a broad perspective of the various benefits of MES implementation and its key application areas.

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Manufacturing Safety

Case study

Manufacturing Safety

ITC Infotech designed a computer vision solution using Deep Learning technique involving Image Processing and Convolution Neural Networks, which provided the probability of a pump having a leak and also the leak localization zone for an Oil Pump. The solution provided a manifold improvement of the existing manual process in saving both operational cost and time.

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Advanced Process Control

Case study

Advanced Process Control

Paper is a thin material produced by pressing together moist fibres of cellulose pulp derived from wood, rags or grasses, and drying them into flexible sheets. It is a versatile material with many uses, including writing, printing, packaging, cleaning, decorating, and a number of industrial and construction processes. Paper is characterized by properties like caliper (thickness in μm), GSM (grams per square metre) and moisture content (%) which determine properties like stiffness (ability for a sheet of paper to resist bending), bulk (weight per unit volume), tensile strength (maximum stress to break a strip of paper sheet, depends on fibre orientation), edge wick (Water absorption at the edge) and many others. Regression model that explained the statistical relationship between moisture content and operational parameters was established. Once established and validated, the model parameters operating ranges to achieve a specific range of moisture was arrived at by an optimization algorithm and the same were implemented during the production process.

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Deep Learning Based Computer Vision Techniques for Defect Detection & Monitoring

Whitepaper

Deep Learning Based Computer Vision Techniques for Defect Detection & Monitoring

The major threat that occurs in pipelines is leakage. The effects of leakage go beyond repair expense and cost of lost oil or gas. It also significantly affects the human lives and environment. In this white paper we have devised a Deep Learning-based solution using Convolution Neural Networks(CNN) and image processing techniques to detect and localize the leakages in oil & water pipelines.

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