Performance based efficiency monitoring system for Manfacturing industry

Business challenges

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Data collection and management: Collecting and managing data from multiple manufacturing plants and departments can be a challenge, especially if the data is not centralized or if the plants and departments are using different systems for data collection and management.

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Data analysis and interpretation: Analyzing and interpreting data from multiple plants and departments to make informed business decisions can be difficult, especially if the data is not in a consistent format or if it is not easily comparable.

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Limited visibility: Limited visibility into the performance of individual plants and departments can make it difficult to identify and address performance issues in a timely manner.

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Inefficiency: Manual monitoring can lead to inefficiency and inaccuracy, as it requires a significant amount of time and resources to collect, analyze, and interpret the data.

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Difficulty in identifying problem areas: Complex and un-visualized reports can make it difficult to identify problem areas, as it is hard to identify patterns and trends in the data.

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Lack of real-time data: Manually monitoring performance means that data is not available in real-time, making it difficult to quickly identify and address issues as they arise.

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Lack of technology: Lack of proper technology to track, monitor and analyze data from multiple plants and departments can make it difficult to get the accurate and real-time information.

Solution Overview

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One of the world's largest manufacturers aimed a strategic vision of improving their plant’s performances through the development of a plant efficiency monitoring system.

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The solution tracks the performance of each plant and identifies inefficiencies within specific streams and shifts within the plant.

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Replacement of manual maintenance of reports and analytics with automated report generation to determine the top-performing plants and Target KPIs achievements among plants with more accuracy and seamless manner.

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This solution automates report generation regarding the performance of each stream in particular shifts for each plant-based and overall plants.

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The internal manager can view best performing streams and shifts among overall plants in accuracy and error-free due to the system-generated reports and analytics replacing manual work.

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Through the reporting system, one can set target KPIs and monitor actual KPIs met for both streams and plant-wise data daily

Business Impact

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Improved visibility: With a centralized system, managers and executives can easily access real-time performance data from all plants, which allows them to quickly identify any issues and make informed decisions.

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Increased efficiency: By monitoring performance data in real-time, managers can quickly identify and address bottlenecks, inefficiencies, and other issues that may be impacting production.

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Better communication: A centralized system allows managers to easily share performance data and reports with other departments and stakeholders, which improves communication and collaboration.

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Reduced downtime: By identifying and addressing issues early on, a centralized performance monitoring system can help to reduce downtime and improve overall plant efficiency.

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Better decision making: With all the data in one place, one can have better insights to make strategic decision which can impact the company positively.

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Improved accountability: By setting target KPIs and monitoring performance, managers can hold individual departments and employees accountable for their performance and take appropriate action if needed.

Technology Stack

Key Features

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Plant Level- Dashboard

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Performance based Ranking recognition

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Stream wise Reports

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Update Target and Actual KPI

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Export data

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Refined Filtering of reports

Trusted and Proven Engagement Model

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

Awarded Bronze Trophy at CII National competition on Digitization, Robotics & Automation (DRA) – Industry 4.0

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50+

AI & ML
Engineers

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40+

AI & ML
Projects for
reputed Clients

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5 yrs

in AI & ML
Engineering

Awarded as Winner among 1000 contestants at TechSHack Hackathon

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