实例探究 > Aluminerie Alouette implements STATISTICA Data Miner and MSPC

Aluminerie Alouette implements STATISTICA Data Miner and MSPC

公司规模

1,000+

地区

America

国家

Canada

产品

STATISTICA Data Miner
MSPC
STATISTICA Enterprise

技术栈

Automated Neural Networks

实施规模

Enterprise-wide Deployment

影响指标

Cost Savings
Environmental Impact Reduction
Productivity Improvements

技术

分析与建模 - 数据挖掘
分析与建模 - 机器学习
分析与建模 - 预测分析

适用行业

金属

适用功能

流程制造
质量保证

用例

机器状态监测
预测性维护
过程控制与优化

服务

软件设计与工程服务
培训

关于客户

Aluminerie Alouette, established in 1992, is an independently operated company producing primary aluminum. With a workforce of 1,000 employees and an annual production capacity exceeding 600,000 tons, it stands as the largest employer in Sept-Îles, Canada, and the leading aluminum smelter in the Americas. The Sept-Îles smelter is renowned globally for its energy consumption efficiency and state-of-the-art technology, surpassing government environmental standards. Aluminerie Alouette has been utilizing STATISTICA Enterprise for several years to monitor key performance indicators and control the production process efficiently.

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挑战

Aluminerie Alouette needed to continuously improve its production processes to stay among the worldwide leaders in aluminum manufacturing. The company faced the challenge of understanding the influence of several hundred inputs on the aluminum manufacturing output. Some inputs could be controlled, such as the dosage of additives and energy management, while others, like outside temperature and raw material composition, could not. To address this, Aluminerie Alouette required a solution that could identify significant inputs and develop multivariate models to monitor key performance indicators.

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解决方案

To better understand the influence of various inputs on the aluminum manufacturing process, Aluminerie Alouette augmented its existing STATISTICA Enterprise with STATISTICA Data Miner and MSPC software for multivariate analyses. These StatSoft modules were expected to identify inputs with significant influence on key performance indicators and develop multivariate models for monitoring additional indicators. The implementation of these modules allowed Aluminerie Alouette to conduct several analyses, validating that STATISTICA Data Miner and MSPC met their needs. Automated neural networks in STATISTICA enabled the development of models representing different operating scenarios based on historical data. These models allowed for the adjustment of relevant inputs without compromising the quality of operations and facilitated medium-term production predictions considering future events.

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运营影响

The implementation of STATISTICA Data Miner and MSPC initiated a new approach at Aluminerie Alouette to identify the source of problems related to the production process.
The software solutions provided a better understanding of the interaction between different inputs, allowing for more informed decision-making.
The deployment of models enabled the exploration of different scenarios by extrapolating outside the current domain, enhancing operational flexibility.
Training on StatSoft solutions and a good understanding of the domain being analyzed were crucial for achieving significant and interesting results.
The use of STATISTICA Data Miner made it easy to identify parameters that significantly impact various aspects of the process, although user expertise was essential for accurate analysis.

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数量效益

Aluminerie Alouette achieved an annual production capacity of over 600,000 tons of aluminum.
The company employs 1,000 people, making it the largest employer in Sept-Îles, Canada.

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