- 第一段階。
- 建筑物
- 应用设计
- 应用程序编辑器
- 郁金香应用程序编辑器介绍
- 创建新的郁金香应用程序
- 如何在应用程序编辑器和播放器中使用键盘快捷键
- 郁金香中的多语言功能
- 步骤
- 小装饰
- 什么是 Widget?
- 输入小工具
- 嵌入式小工具
- 按钮小工具
- 如何配置小工具
- 为步骤添加输入部件 更新资料
- 什么是交互式表格小工具?
- Product Docs Template
- 如何嵌入视频
- 如何在应用程序中嵌入分析功能
- 使用文件
- 动态填充单选或多选 widget
- 如何使用复选框小工具
- 如何添加条形码小工具
- 如何在步骤中添加网格小部件
- 如何在应用程序内和应用程序之间复制/粘贴内容
- 如何在步骤中添加仪表小部件
- 自定义部件概述 更新资料
- 创建签名表步骤
- 使用输入部件进行数据验证 更新资料
- 记录历史小工具概述
- 表格步骤的技术细节
- 如何在应用程序中添加图片
- 如何使用电子签名小工具
- 应用程序中的数字格式 更新资料
- 教科文组织
- 什么是触发器?
- 阶跃触发器
- 应用程序级触发器
- 小部件触发器
- 应用程序过渡指南
- Capture App Screenshot
- 计时器触发器
- 如何添加设备触发器
- 如何通过条件(If/Else 语句)添加触发器
- 触发器编辑器中的操作和转换列表
- 最常见的十大触发因素是什么?
- 如何通过触发器设置部件颜色
- 如何发送电子邮件
- 如何为 Tulip 用户设置短信通知
- 如何从触发器打印步骤
- 如何在应用程序编辑器中使用表达式编辑器
- 表达编辑器的技术细节
- 应用程序编辑器中的完整表达式列表
- 使用日期时间表达式
- 类型化表达
- 使用数组和对象表达式
- 在触发器中处理时间
- 支持的自定义日期格式
- 如何完成应用程序
- 如何通过设备摄像头扫描条形码和 QR 码
- 如何在触发器中添加正则表达式
- 在郁金香应用程序中使用应用程序信息
- 如何使用触发器调用连接器函数
- 变量
- 解决问题
- 达蒂(印度教女神)。
- 连接器
- 分析
- 视觉
- 设备监测
- 受管制行业
- 副驾驶站在第一线。
- 自动化
- 进口中的出口
- 运行应用程序
- 管理
- Developers
- Connect to Software
- Connect to Hardare
- Edge Devices
- 支持的设备
- 可与郁金香配合使用的即插即用设备列表
- 创建和支持设备驱动程序
- 郁金香中的设备驱动程序支持
- 如何设置条形码扫描仪
- 使用串行驱动程序
- 如何将斑马打印机与 Tulip 集成
- 使用 Zebra 网络打印机驱动程序
- 使用 Zebra GK 系列标签打印机驱动程序
- 使用 USB 波贝盒驱动程序
- 使用康耐视 In-Sight 2000 驱动程序
- 如何配置康耐视和 Tulip
- 使用 MT SevenExcellence PH 计驱动程序
- 使用通用 ADC 驱动程序
- 使用欧米茄 HH806 温度计驱动器
- 使用数字卡尺驱动器
- 如何设置通用 TS05 蓝牙测温枪
- 使用康耐视 DataMan TCP 驱动程序
- 为 Windows Tulip Player 设置三丰 U-WAVE 接收器
- 使用布雷克内尔 PS25 称重驱动器
- 使用 RFID 驱动程序
- 使用Kolver EDU 2AE/TOP/E驱动程序
- 使用 USB 脚踏板驱动程序
- 使用 Torque 开放协议驱动程序
- 使用 Dymo M10 USB 电子称驱动程序
- 使用康耐视 In-Sight 驱动程序
- 使用 Telnet 驱动程序
- 使用通用 I/O 驱动程序
- 如何设置科尔弗扭矩控制器
- 使用 Insize 多通道卡尺驱动器
- 使用 Dymo S50 USB 电子称驱动程序
- 斑马 Android DataWedge 配置
- 将三丰数字卡尺与三丰 U 波驱动器配合使用
- 如何添加奥豪斯秤并将输出存储在变量中
- 温湿度传感器单元测试
- Troubleshoot
- Nodo Rosso.
- 创建可重复使用的组件
- 使用应用程序接口
- Edge Driver SDK
- 技术和信息技术文件
- 指南
- 图书馆
- 使用郁金香图书馆 更新资料
- Laboratory Operation App Suite
- 图书馆藏书
- 图书馆应用程序
- 教科书上的例子
- 应用解决方案
- CMMS 应用程序包
- Zerokey solutions
- 成果的可见性
- 物品委託電子申告(eBR)申請書類一式
- 盈科 CAPA Lite
- 5 为何使用人工智能进行根源分析
- 利用人工智能进行简单的缺陷报告
- 业务案例生成器
- 轮班启动会议
- 看板应用程序套件
- 简单的 OEE 控制面板
- Arena BOM 解决方案
- 设备管理应用程序套件
- 简单核对表
- 清单管理套件
- 考勤管理简单解决方案
- 包装与装运图书馆应用
- CAPA 管理
- 移动照相机应用程序
- OEE 计算器
- 每小时生产记分卡
- 材料反冲
- 质量事件仪表板
- 首次通过产量申请
- 采光
- 培训解决方案
- 数字系统库存
- 视觉定位跟踪
- 数字系统访问管理
- 材料管理
- 工具与资产经理
- 优质活动管理
- 带断光传感器的步进推进器
- 数字秒表
- 审核清单
- 卡塔纳企业资源规划应用程序
- 高级别基线评估
- 物料清单管理
- 安全事故经理
- Composable Lean
- Composable Mobile
- 如何申请
- 可堆肥 MES
- 制药行业的 MES 系统
- 连接器和单元测试
- Planeus 单元测试 更新资料
- COPA-DATA 连接器 新
- Veeva 连接器
- Inkit 连接器
- MRPeasy 连接器
- Oracle 融合连接器
- LabVantage 连接器和单元测试
- 谷歌聊天连接器
- Salesforce 连接器
- Litmus 概览
- eMaint 连接器
- eLabNext 连接器
- Acumatica ERP 连接器
- CETEC 连接器
- PagerDuty 连接器
- NiceLabel 集成
- Aras 集成概述
- SDA 集成
- 尼米乐队单元测试
- 竞技场整合 更新资料
- 条码扫描器单元测试
- 脚踏板单元测试
- 开始在 RealWear 头戴式耳机上使用郁金香
- 空气台连接器
- 希波连接器
- 调酒师集成
- SAP S/4 HANA 云连接器
- RFID 扫描仪单元测试
- Jira 连接器
- 斑马标签打印机单元测试
- 谷歌翻译连接器
- MSFT Power Automate
- OpenAI 连接器
- 谷歌日历连接器
- 郁金香应用程序接口单元测试
- Duro PLM 单元测试
- HiveMQ 单元测试
- 与 NetSuite 集成
- 康耐视单元测试
- PowerBI 桌面集成
- ProGlove 单元测试
- Fivetran 集成
- ParticleIO 集成
- Google Drive 连接器
- 雪花连接器 更新资料
- SAP SuccessFactors 连接器
- ZeroKey Integration
- 谷歌地理编码连接器
- 谷歌工作表连接器
- 如何将 Tulip 与 Slack 整合
- HighByte 智能枢纽单元测试
- LandingAI 单元测试
- LIFX 单元测试(无线灯)
- 微软日历连接器
- M365 Dynamics F&O 连接器
- Microsoft Outlook 连接器
- Microsoft Teams 连接器
- 使用 Oauth2 将 Microsoft Graph API 连接到 Tulip
- Microsoft Excel 连接器
- 网宿应用程序和连接器
- OpenBOM 连接器
- 称重秤单元测试
- InfluxDB 连接器
- Augury 连接器
- 连接器
- 舍弗勒 Optime 连接器
- MongoDB Atlas 连接器
- MaintainX 连接器
- Twilio 连接器
- SendGrid 连接器
- 安慰连接器
- 如何为 RealWear 头戴式耳机设计郁金香应用程序
- OnShape 连接器
- 可定制的小部件
- 调度自定义小工具 新
- 时间轴小工具
- json 树查看器小工具
- 看板任务管理小工具
- 徽章小工具
- 高级计时器小工具
- 分段按钮自定义小工具
- 动态仪表自定义小工具
- 小吃店小部件
- 变化探测器单元测试
- 状态颜色指示器 设备测试
- 输入长度检查单元测试
- 计算器自定义部件单元测试
- 图像注释小工具单元测试
- 精益仪表板小工具
- Looper 单元测试
- 秒表单元测试
- 数字输入单元测试
- 数字键盘单元测试
- 径向测量仪
- 菜单单元测试步骤
- SVG 小工具
- 文本输入单元测试
- 工具提示单元测试
- 作业指导 照顾要点 单元测试
- 书面电子签名小工具单元测试
- ZPL 查看器单元测试
- 简单折线图小工具
- 货架自定义小工具
- 滑块小工具
- NFPA 钻石定制小工具
- 通过 - 失败 自定义小工具
- 简单计时器自定义小工具
- Nymi Presence集成小工具
- 自动化
Imagine you’re a plant manager at a medium-sized company. There are multiple operations for production that produce various items and while the company is doing well, you know there are areas for improvement. There is a high scrap rate, excessive defect parts, and you’re not sure which areas of production are maximizing their time most efficiently. In order to understand what is happening and how you can take measures to improve, you need visibility into various areas of performance in your production.
Performance visibility is the ability to track basic facts about production in real time. It involves applications that collect information about quality, delivery, and productivity of work centers. The information gathered from this use case is often measured against established targets or goals for a defined subject. Performance visibility as a use case first encompasses various types of performance data within an operation. This data should reflect your KPIs, such as parts per hour/shift/operator, on-time orders, scrap rate, quality, OEE, FPY, or throughput. The other part of performance visibility is visualizing your data with analytics, dashboards, or other tools. Visualizing production data provides a way to measure how well a line, station, machine, or operator is performing against either a target or historical average. Gathering this data is crucial for taking action on low performing assets and correcting areas to meet your goals. Successfully implemented performance visibility can increase ROI by addressing concerns such as labor costs, scrap, costs, cycle time, and more.
While performance visibility can apply to multiple parts of an operation and use different features within Tulip, visualizing the data with Analytics is an essential part of gaining insight that informs decision making, resolves issues, and reveals opportunities for improvement. Seeing real-time performance data compared against historical data should allow you to understand root causes and prioritize improvements.
Impact and Requirements
Consider the following questions:
- Do you know if cells/lines/machines are meeting their production targets?
- Do track quality (down to the operator level)?
- Do you know where work orders are in real time?
- Can you track cycle time for all of your lines and assemblies?
- Do you know how close you’re hitting targets month-to-month?
Seeing the data leads you to figure out why issues or discrepancies are present and react quickly to correct your course. Companies can drive results through their performance data by determining the priority for improvement and where to start. Tulip allows companies to define their own approach to suit particular needs while also providing ways to standardize and scale this process across an organization. Because performance visibility use cases prioritize collecting basic information, they are suitable for a large number of different manufacturing types and industries. Higher volume production especially benefits from performance visibility, especially as data is refined and gets more granular overtime. Lower volume production also benefits when users focus less on earned value and more on real-time data.
The ideal MVP approach in Tulip should be broken up by use case to resource needs as apps get more complex. Creating different apps for different personas ensures only relevant information is available for each area of operation. Leveraging data from dashboards can inform your company’s KPIs, such as:
- Uptime percent as it relates to downtime root causes
- Production Output, e.g. Units per Hour
- Defect Rate (minimized)
- Cycle time
Performance visibility doesn’t require expert skill or experience with Tulip to get started. Analytics are fairly easy to implement once you have data collected, which you can do using Completions or Tables. The most crucial thing to focus on before building this visibility is identify what area you want to increase insight. Start by defining the subject you need to measure (e.g. station, machine, individual, work center, etc.) and then determine the unit of measurement (e.g. output by week, uptime %, etc.). For regulated industries, keep in mind that you may require more scrutiny with operator inputs to collect data.
How to Get Started
Performance visibility requires two things: data and visualizations. Any other features are dependent on the subject and its measurement. Therefore, it’s crucial to narrow down what you care about to define the problem you want to solve. Choose features that will inform questions about your subject. You can start with existing data that’s pulled each week or month to make it available at will. The deployment and path to value can vary depending on if you are seeking to cut costs or increase revenue. Follow these steps to ensure your process has a solid foundation to begin with:
1. Define the subject you want to measure. Start with a more broad subject to measure and get more granular as needed. These can include:
- A station
- A machine
- An individual
- A work center
- An existing KPI
2. Determine the unit of measurement. For example:
- The downtime percentage of a machine
- An individual’s output of units by week
- The ratio of good parts to bad parts by part ID
3. Determine the best visualization. This may be a single number or a chart.
4. Deploy, monitor data, and iterate. Gather or refine the subject and measurements in order to focus on simple parts of your process. Always remember to start simple.
Only after successfully deploying an app and optimizing its results, should you consider advancing and integrating with other systems. These can include Andon alerting, Blue Print dashboard, Kanban system, and more. You can also begin to build on existing data and real-time events to provide more context and inform decisions that impact other areas of production, such as importing data from a Tulip table into Power BI. This can quickly get complex, so begin with simple measurements and grow from there.
Tulip Resources
Whether you want to learn more about Tulip features to build performance visibility apps or you want to use Tulip’s ready-made templates, we have the tools to help you get started.
Videos
University Courses
Library Apps
- Performance Visibility Terminal
- Shared Performance Visibility Terminal
- Consolidated Performance Visibility Terminal
- Performance Visibility Dashboard
- Mobile Hourly Production Scorecard
Examples
Did you find what you were looking for?
You can also head to community.tulip.co to post your question or see if others have faced a similar question!
Analytic
Analytics are live updating graphs and metrics calculated based on app data, Table data, and machine data. Analytics can be embedded and dynamically filtered within an application.
App Completion
App Completions are a mechanism to store immutable data from a Tulip app. When an app is completed, all Variable's current values will be stored in the app completions tab. This completion data can be analyzed in Analytics.
By default, after a Completion users will be brought back to the Begin Screen of your application. This behavior can be adjusted with other Transition types.
Tulip Tables
Tulip Tables are a global location to store your production data. Tables are made up of Records (rows). A single can be accessed from multiple apps or stations at the same time.