{"id":27311701,"url":"https://github.com/sushant1827/machine-learning-for-predictive-maintenance","last_synced_at":"2025-04-12T06:23:21.142Z","repository":{"id":270602180,"uuid":"910872520","full_name":"sushant1827/Machine-Learning-for-Predictive-Maintenance","owner":"sushant1827","description":"Demonstrate the application of machine learning on a real-world predictive maintenance dataset, using measurements from actual industrial equipment.","archived":false,"fork":false,"pushed_at":"2025-01-01T17:35:08.000Z","size":1748,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-08T13:51:39.226Z","etag":null,"topics":["binary-classification","classification-report","confusion-matrix","data-imbalance","data-visualization","decision-tree-classifier","exploratory-data-analysis","feature-engineering","feature-importance","feature-selection","gradient-boosting-classifier","imbalanced-data","multi-class-classification","roc-auc-curve"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sushant1827.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-01-01T17:33:13.000Z","updated_at":"2025-01-13T11:52:14.000Z","dependencies_parsed_at":"2025-01-01T18:40:00.800Z","dependency_job_id":null,"html_url":"https://github.com/sushant1827/Machine-Learning-for-Predictive-Maintenance","commit_stats":null,"previous_names":["sushantdhumak/predictive_maintence_with_machine_learning","sushant1827/machine-learning-for-predictive-maintenance","sushantdhumak/machine-learning-for-predictive-maintenance"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sushant1827%2FMachine-Learning-for-Predictive-Maintenance","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sushant1827%2FMachine-Learning-for-Predictive-Maintenance/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sushant1827%2FMachine-Learning-for-Predictive-Maintenance/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sushant1827%2FMachine-Learning-for-Predictive-Maintenance/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sushant1827","download_url":"https://codeload.github.com/sushant1827/Machine-Learning-for-Predictive-Maintenance/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248526090,"owners_count":21118808,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["binary-classification","classification-report","confusion-matrix","data-imbalance","data-visualization","decision-tree-classifier","exploratory-data-analysis","feature-engineering","feature-importance","feature-selection","gradient-boosting-classifier","imbalanced-data","multi-class-classification","roc-auc-curve"],"created_at":"2025-04-12T06:23:20.239Z","updated_at":"2025-04-12T06:23:21.133Z","avatar_url":"https://github.com/sushant1827.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\n\n### **Machine Learning for Predictive Maintenance**\n\n---\n\n#### **Brief Description**\n\nThis dataset reflects real predictive maintenance encountered in the industry with measurements from real equipments. The features description is taken directly from the dataset source.\n\nDataset Link:\nhttps://archive.ics.uci.edu/dataset/601/ai4i+2020+predictive+maintenance+dataset\n\n---\n\n#### **Feature Variables**\n\n**Air temperature** [K]: Generated using a random walk process later normalized to a standard deviation of 2 K around 300 K\n\n**Process temperature** [K]: Generated using a random walk process normalized to a standard deviation of 1 K, added to the air temperature plus 10 K.\n\n**Rotational speed** [rpm]: Calculated from a power of 2860 W, overlaid with a normally distributed noise\n\n**Torque** [Nm]: Torque values are normally distributed around 40 Nm with a σ = 10 Nm and no negative values.\n\n**Tool wear** [min]: The quality variants H/M/L add 5/3/2 minutes of tool wear to the used tool in the process.\n\n---\n\n#### **Target Variables**\n\n**Machine failure** : Failure or No failure (to perform binary classification)\n\n**Failure Type**: Type of failure (to perform multiclass classification).\n\n---\n\nThe machine failure type are as mentioned below\n\n**Tool wear failure** (TWF): The tool will be replaced on failure\n\n**Heat dissipation failure** (HDF): Heat dissipation causes a process failure\n\n**Power failure** (PWF): The product of torque and rotational speed (in rad/s) equals the power required for the process.\n\n**Overstrain failure** (OSF)\n\n**Random failures** (RNF): Each process has a chance of 0,1 % to fail regardless of its process parameters.\n\n----------------------------------------------------------------------\n\n#### **Additional Variables**\n\n**UID**: Unique identifier ranging from 1 to 10000\n\n**Product ID**: Consists of letters L, M, or H for low (50% of all products), medium (30%) and high (20%) as product quality variants and a variant-specific serial number\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsushant1827%2Fmachine-learning-for-predictive-maintenance","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsushant1827%2Fmachine-learning-for-predictive-maintenance","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsushant1827%2Fmachine-learning-for-predictive-maintenance/lists"}