Ankara - Çankaya HQ
Senior Robotics Reliability and Verification Engineer
Who We Are
Hello! We are OPLOG, Turkey’s leading tech-enabled fulfillment startup enabling e-commerce brands across Europe to streamline and optimize their post-purchase fulfillment operations. We enable e-commerce brands to operate in various markets without physical boundaries through our international fulfillment networks with the ability to track all the inventory and operational processes.
Recognized by Deloitte as Turkey’s fastest-growing tech company, we raised €11 million from one of Turkey’s leading investment funds, Esas Private Equity. Our goal is to be #1 best fulfillment technology in the industry. But wait, there is more! We work with global companies such as SONY, Tupperware, Rossmann, and many local champions.
As one of the first companies to utilize proprietary robotics technology in our fulfillment centers, we aim to support and propel brands/companies beyond industry 4.0 transformation. Similarly, by creating a reliable and connected fulfillment infrastructure, we can help big and small brands/companies scale their businesses by allowing them to focus on their products, not the delivery journey.
What You'll Do
- Validate mechatronic designs and systems using a fact-based and data-driven approach to ensure their reliability and performance.
- Design, utilize, and maintain test facilities, instruments, and rigs for conducting various validation tests.
- Establish the technological boundaries of our designs by conducting stress tests to assess their limits and performance under different conditions.
- Perform failure analysis of robots deployed in the field to identify root causes and contribute to continuous improvement efforts.
- Collaborate closely with the product, R&D, and software teams to ensure comprehensive system validation and integration.
- Conduct FMEA analysis to define, predict, and focus on potential failure modes, enhancing the design's robustness and reliability.
- Conduct Design FMEA (DFMEA) by breaking down the Warehouse Robot into manageable components, analyzing potential failure points.
- Perform Reliability Prediction analysis (MTBF analysis based on widely-accepted reliability prediction standards) to assess and optimize product reliability during early development stages and later for complete system MTBF assessment.
- Perform Maintainability Prediction Study to compute various repair and maintenance metrics, such as MTTR, to help optimize maintenance policies and improve system uptime and availability.
- Utilize MIL-HDBK-472 for valuable insights into critical metrics.
- Conduct Accelerated Life Testing (ALT) Analysis to evaluate product performance under various stress conditions such as temperature, vibration, or humidity, predicting and assessing product performance over time.
- Utilize Weibull analysis for analyzing life data to predict failure profiles, the probability of a unit operating at a given time, the mean life of a unit, the number of expected failures over a specific period, and determining appropriate warranty periods.
Who You Are
- Minimum of 5 years of experience in the related field.
- Proficiency in utilizing and interpreting reliability standards commonly used in the Automotive Industry, such as SAE J1739, AIAG, and MIL-STD-1629A.
- Familiarity with Reliability Software tools and their application in conducting reliability predictions and analyses.
- Strong analytical skills to conduct failure analysis and FMEA (Failure Modes and Effects Analysis) studies effectively.
- Demonstrated experience in designing and maintaining test facilities, instruments, and rigs for validation purposes.
- Solid understanding of stress testing and Accelerated Life Testing (ALT) methods for product evaluation.
- Ability to collaborate with cross-functional teams, including product, R&D, and software teams, to ensure comprehensive system validation.
- Knowledge of Weibull analysis for predicting failure profiles, product lifetime, and warranty period determination.
- Experience in conducting Maintainability Prediction Studies to optimize maintenance policies and improve system uptime and availability.