--- description: Senseye PdMを実際に使用したユーザーのレビューから、製品の機能や価格、メリットデメリットをご覧いただけます。類似製品との比較も簡単、ぴったりのSaaSが見つかるはず！ image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: Senseye PdMとは？ | 機能や料金、導入事例をご紹介【キャプテラ】 --- 現在地表示: [ホーム](/) > [IoTシステム](/directory/31016/iot/software) > [Senseye PdM](/software/193501/senseye-pdm) # Senseye PdM Canonical: https://www.capterra.jp/software/193501/senseye-pdm > Senseye PdMは、資産の状態を規模に応じてリアルタイムで自動的にモニタリングおよび予測するため、予定外のダウンタイムを削減することができます。 > > 評価：5人のユーザーによる評価は**4.4/5**。**おすすめ度**で最高の評価。 ----- ## 概要 ### Senseye PdMの対象ユーザー Senseyeは、自動車、製造、重工業などの業界において世界中のFortune 500企業の顧客が毎週予定外のダウンタイムとメンテナンス・コストを何百万ドルも削減することができるよう支援しています。 ## 簡単な統計と評価 | 測定基準 | 評価 | 詳細 | | **総合評価** | **4.4/5** | 5 レビュー | | 使いやすさ | 4.2/5 | レビュー全体に基づく | | カスタマー・サポート | 5.0/5 | レビュー全体に基づく | | 価格の妥当性 | 4.0/5 | レビュー全体に基づく | | 機能 | 4.4/5 | レビュー全体に基づく | | おすすめ率 | 80% | (8/10 おすすめ度) | ## 企業情報 - **キャプテラについて**: Senseye - **ロケーション**: Southampton, 英国 - **設立**: 2014 ## ビジネスコンテキスト - **価格プラン**: $7.50 - **対象となる企業**: 51～200, 201～500, 501～1,000, 1,001～5,000, 5,001～10,000, 10,000+ - **デプロイとプラットフォーム**: クラウド、SaaS、ウェブベース, Android（モバイル）, iPhone（モバイル）, iPad（モバイル） - **サポートされる言語**: 英語 - **利用可能な国**: アメリカ合衆国, イギリス, インド, オーストラリア, カナダ, ドイツ, ブラジル, メキシコ, 中国, 日本 ## 機能 - Third-Party Integrations - ダウンタイム追跡 - データのインポート／エクスポート - データの取得と転送 - データ管理 - トレンド分析履歴 - ビッグデータ分析 - メンテナンスのスケジューリング - モニタリング - モバイル・アクセス - リマインダー - レポートと統計 - 予測メンテナンス - 作業発注管理 - 点検管理 ## サポートのオプション - メール/ヘルプデスク - ナレッジベース - 電話サポート - 24時間対応（オペレータ） - チャット対応有 ## Category - [IoTシステム](https://www.capterra.jp/directory/31016/iot/software) ## 関連カテゴリー - [IoTシステム](https://www.capterra.jp/directory/31016/iot/software) - [予防保全システム](https://www.capterra.jp/directory/31023/preventive-maintenance/software) - [OEEソフトウェア](https://www.capterra.jp/directory/31339/oee/software) - [メンテナンス管理システム](https://www.capterra.jp/directory/30058/maintenance-management/software) ## 代替製品 1. [The Asset Guardian (TAG)](https://www.capterra.jp/software/148747/the-asset-guardian-tag) — 4.4/5 (12 reviews) 2. [MaintainX](https://www.capterra.jp/software/179296/getmaintainx) — 4.8/5 (1005 reviews) 3. [Fiix](https://www.capterra.jp/software/74916/fiix) — 4.5/5 (628 reviews) 4. [UpKeep](https://www.capterra.jp/software/145635/upkeep) — 4.6/5 (1321 reviews) 5. [eMaint CMMS](https://www.capterra.jp/software/100468/emaint-cmms) — 4.5/5 (384 reviews) ## レビュー ### "Senseye PdM" — 5.0/5 > **Dylan** | *2021年6月30日* | 包装と容器 | おすすめ評価：9.0/10 > > **良いポイント**: The following features have been used most effectively within Smurfit Kappa: - Compare Dashboards - Thresholds and Prognostics - Trend and anomaly detections > > **改善点**: The system performs a 120 hour learning period for each asset that in on-boarded to the system. In this time, the system 'learns' what the 'normal' operating levels (vibration and current) are for each unique asset. If an asset is in poor condition when the system is installed, however, the system learns that the poor condition is the normal condition. > > As a result of the successful implementation of the Senseye PdM system at Jupiter Road, a number of potential breakdowns were avoided. With the support of the system, lost time has been avoided by completing preventative maintenance during periods of scheduled downtime, prior to the degradation and catastrophic failure of an asset. Further to the system’s ability to detail the issues with the site’s assets, it has also been used to confirm if the machines are in good health – and how exactly they operate under various conditions. This assurance has helped the team to confidently run the corrugator, to maximise production output. ----- ### "use of Senseye within the steel industry" — 4.0/5 > **David** | *2021年6月30日* | 鉱業、金属 | おすすめ評価：7.0/10 > > **良いポイント**: Senseye as an application is important to the future of industries like steel, where margins are tight and resources are limited. This sort of predictive application will be critical to the success of the industry as it will give us confidence in the condition of our assets and allow us, along with the use of other condition systems, to carry out targeted maintenance based on the actual condition of our assets. This will have a significant benefit to the availability of our assets and minimise unplanned outages. > > **改善点**: I find the user interface to be a bit 'clunky' , if it could be easier to get to the issue and get the feedback in a slicker way that would make it much easier. As mentioned the notification system needs to be developed to notify by exception, and also look at different ways to send the notifications. > > One of the strongest elements of Senseye is the team behind it, they have worked well with our team in integrating and moulding Senseye to work in the hugely varying environment of the steel industry. ----- ### "Using Senseye in a CNC machining context" — 4.0/5 > **Jan** | *2021年6月29日* | 機械工業 | おすすめ評価：6.0/10 > > **良いポイント**: the ease of integration and setup. the easy to use application The support and friendly nature of the team @ Senseye > > **改善点**: not getting the results we needed and it seems to have been over promised at sales pitches > > despite not having reached the results we needed I would still recommend their tool as long as you have made sure the Q of the data is adequate and able to pinpoint the failure you try to predict. It is not a magic system that sees failures out of any data, as it is often sold. ----- ### "Great system that gievs me a good overview of the condition of motors and gearboxes" — 4.0/5 > **Tim** | *2021年6月28日* | 化学 | おすすめ評価：9.0/10 > > **良いポイント**: The alert system that points me to the problem areas is invaluable, also the fact that i can scan over all the motors and gearboxes on my line without having to test each one individually is brilliant > > **改善点**: Id Like to be able to see the condition of all motors and gearboxes on one page as a quick glance rather than scrolling down a list > > Great so far and as we implement more features it is becoming more impressive ----- ### "Intuitive Senseye Software Scales Your Predictive Maintenance" — 5.0/5 > **Andy** | *2019年9月1日* | 機械・産業工学 | おすすめ評価：10.0/10 > > **良いポイント**: The intuitive dashboard is excellent for front line users to gain insights quickly and direct their attention to the important few assets thereby freeing up their limited resources. The feedback loop via the maintainers dashboard is great to alert the support team at Senseye of the type of anomalies found, this information then leverages the power of their machine learning algorithms to get from Predictive to Prognostic. > > **改善点**: Most of my experience is around the front end where the engineers and maintainers interact with the dashboard. The latest iteration has improved over time to fit the end users needs and become more intuitive. All of my concerns of a couple of years ago have now been improved due to the excellent support team at Senseye. It's great that they have engineers with predictive technology backgrounds that understand the challenges that users face daily in an industrial environment. > > I was aware of Senseye as a software application to scale prediction in industry and came across users when I was training front line engineers at Nissan UK, Senseye was new to them and like most they were not open to change. That soon turned around when we started seeing real results coming in as the Senseye software gained more data insights that they could see resulting in avoiding unplanned events. I've found it very easy to navigate and as a former predictive practitioner could see the enormous benefits that scaling PdM brings; this was something we could only dream of just ten years ago\! ## リンク - [Capterraで表示する](https://www.capterra.jp/software/193501/senseye-pdm) ## このページは以下の言語で利用できます | ロケール | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | es | | | es-AR | | | es-CL | | | es-CO | | | es-CR | | | es-DO | | | es-EC | | | es-MX | | | es-PA | | | es-PE | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | it | | | ja | | | nl | | | nl-BE | | | pt | | | pt-PT | | | sv | | ----- ## 構造化データ