Opcenter

Opcenter Laboratory

Opcenter Laboratory 是一个全面的实验室信息管理系统 (LIMS),可提高实验室吞吐量和质量测试执行效率。

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研究员在实验室中根据实验室信息管理系统 (LIMS) 的质量检测反馈调整配方

无缝支持实验室管理流程

Opcenter Laboratory 可在整个实验室运行过程中提高生产力、效率、质量保证和数据完整性。

实现质量闭环并缩短实验室吞吐时间
Opcenter Laboratory 可在从早期配方开发到在线和离线样品管理整个过程中,确保产品质量,只发布优质批次。在将原材料批次投放生产之前,分析入库交货的样品。

减少样品分析的反馈时间
从样品送达到最终分析结果可用、可验证和传达,提升在整个过程中的实验室效率。LIMS 可缩短反馈时间并加快上市速度。

集成 RD&L 和 MES 以实现质量闭环
加快在线和离线样品分析,以便及时将使用决策传达给制造执行系统 (MES)。必要时采取纠正措施并重新分析批次,以提高质量。对成品进行抽样检查,确保优质的出库质量。

双向连接实验室仪器
避免错误并节省时间。直接与实验室仪器连接,共享样品 ID 并在实验室信息管理系统中登记分析结果,无需手动输入数据。

更有效地管理设备
自动确保跟进所有计划内和计划外的干预措施。Opcenter Laboratory 不接受任何未及时接受干预的仪器的分析结果。

使用操作员资格管理
确保跟进所有运营商资格和更新情况。自动提醒操作员何时重新参加资格考试。Opcenter Laboratory LIMS 不接受资格过期的操作员的分析结果。

统计质量控制 (SQC) 性能和偏差警报
根据西方电力规则,当分析结果(和空白样品)出现偏差时,会收到警报,从而避免废品和返工。Opcenter Laboratory SQC 组件会自动跟进结果,并在出现指示时发送偏差警报。

管理外部用户访问权限
授予外部用户访问 LIMS 以直接检索分析结果/分析证书的权限,从而消除较慢的间接通信(例如,电子邮件)。

可视化呈现趋势
长时间以图形方式可视化呈现 LIMS 分析结果。Opcenter Laboratory 趋势和图表功能有助于轻松识别积极或消极的演变。

创建完整的报告
直接从 Opcenter Laboratory 创建分析证书、性能报告、管理报告等。

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Multi-Discipline Verification and Validation

Bridge the gap between Design and Verification with one platform – document any verification setup

Validation and verification of prototypes or innovation development against the design specifications in hybrid and discrete industries.

In prototype and design verification often a multitude of scientific disciplines are used for the assessment, from imaging to destructive tests. Combining these disciplines into one single testing and verification solution can help you accelerate the innovation cycles and time to market.

Model any type of verification against specification

The industry agnostic Opcenter Laboratory allows you to model any type of testing set up by configuration only. Verify for example the chemical compositions and quantities against targets and tolerance limits. For the same product define i. e. how many charging cycles should be verified against performance specs.

Combine multiple disciplines in sequence and context

One section of your design verification might combine multiple scientific evaluations and need to be considered as a whole, not just as individual test results. In one Verification Request combine for example CT and microscopic image analysis with electrical analysis and chemical and environmental impact evaluations as well as quality control parameters.

Optimize scheduling of testing rigs and conditions

Use the integrated Opcenter Scheduling solution to optimize the planning and execution of all testing on rigs, in specific rooms/ fields/conditions or with equipment. Gain efficiency by avoiding bottle necks and idle times ensuring cost-efficient and in-time use of resources.

Automatically provide input to DVPR

Automatically create documentation of your verification results. Define how the results are combined in reports or report sections to automatically create input for DVPR (Design Verification Plan Reports) and send to design/engineering teams.

Ensure performance requirements and Quality Control for production

Centralize the design validation and verification documentation in one system that holds the DVPR inputs as well as product performance requirements and will handle the future quality control when going to serial production. Provide a single source of truth for both product development and manufacturing.

Full scale LIMS to ensure Quality Control

Use the Opcenter Laboratory LIMS to ensure your products adhere to defined quality standards while enhancing laboratory operational excellence. The MES integrations allow for seamless Quality Control with automated releases and alert handling.

Expedite LIMS activities with automated lab operations

Optimize lab throughput and release times with streamlined workflows, automatic calculations, equipment integrations and rules for decision-making by the system – minimizing human intervention and error.

Centralize R&D collaboration for faster innovation cycles

Allow your global R&D teams to centrally collaborate and learn from each other by making verification documentation easily searchable. Information about what failed is just as valuable as what worked well to accelerate innovation cycles and avoid double trial and error.

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