Explore how we apply systems engineering to solve industry-specific challenges with measurable results.
Challenge: Utilization of multi disciplinar domains to develop a cost effective and robust smart Greenhouse system with cross-country teams.
Solution: We developed an MBSE-driven smart greenhouse system integrating sensors, irrigation control, and light automation, ensuring optimal growing conditions.
Technologies Used: SysML, Arduino, IoT integration, V&V strategy
Impact: Increased yield stability by 30% and enabled remote management capabilities for urban growers.
Developing modern, automated agricultural systems requires the seamless integration of hardware, software, and environmental science. A global client sought to build a cost-effective, robust, and automated smart greenhouse tailored for urban growers. Facing the challenge of coordinating cross-country engineering teams across multiple technical disciplines, they partnered with us to establish a rigorous, model-based system architecture from concept to prototype validation.
Designing an IoT-enabled smart greenhouse demands tight synchronization between hardware structure, sensor integration, automated irrigation, and control software. The project faced two primary hurdles:
We acted as the foundational technical anchor, providing full Model-Based Systems Engineering (MBSE) and requirements engineering. This structured approach managed systemic complexity, allowing the client's internal teams to focus entirely on their core strengths: hardware production and software development.
1. Concept of Operations (ConOps) & Capability Definition
We initiated the lifecycle by defining the Concept of Operations (ConOps) and mapping out operational scenarios for automated light, climate, and irrigation control. From these scenarios, we derived high-level system capabilities, establishing a clear, client-approved baseline before any engineering began.
2. System Analysis & Functional Layout
Utilizing SysML, we conducted a thorough system analysis to define core functions, logical interfaces, and the overall architectural layout. This step ensured all physical components and software blocks would integrate seamlessly.
3. Requirements Cascade, Domain Allocation, & EU Compliance
To translate the architecture into actionable tasks for the engineering domains, we established a strict requirements hierarchy:
4. Verification & Validation (V&V) Strategy
Parallel to requirements definition, we authored targeted Test Cases tied directly to the system requirements. This enabled rigorous validation during the assembly of Prototype 1, ensuring the integrated system met all functional and operational benchmarks.
By decoupling system architecture from domain-level execution, we streamlined the development pipeline for the international team, delivering significant business and technical outcomes:
Challenge: Fragmented product development process hindered scalability and cross-team alignment.
Solution: We integrated the Capella MBSE tool into the UAV manufacturer's development pipeline, aligning requirements, architecture, and simulation models.
Technologies Used: Capella, Simulink, Polarion, MBSE process tailoring
Impact: Reduced design inconsistencies by 45% and improved traceability across engineering artifacts.
A leading Unmanned Aerial Vehicle (UAV) manufacturer faced operational bottlenecks due to a fragmented product development process. As the engineering team scaled, a lack of cross-team alignment and disconnected engineering artifacts risked design inconsistencies. We successfully integrated the Capella MBSE (Model-Based Systems Engineering) tool into their development pipeline, harmonizing requirements, architecture, and models to ensure seamless scalability.
In complex aerospace and defense engineering, alignment is everything. The client's existing product development lifecycle suffered from fragmentation. Without a unified source of truth, the team faced:
Rather than just delivering tools, we engineered a comprehensive transformation process divided into three distinct phases:
1. Capability Building & Cultural Alignment
We initiated the project with targeted peer-to-peer lectures to establish a deep, shared understanding of the Capella modeling environment across the client's engineering teams, ensuring rapid tool adoption.
2. Deep-Dive Gap Analysis
We analyzed the client's existing "way of working" to identify critical process leaks, trace pathway gaps, and architectural inconsistencies.
3. Tailored Workflow Engineering & Automation
After mapping the gaps, we presented a matrix of strategic solutions. The client selected a preferred path focused on deep pipeline integration:
The integration of Capella transformed the client's engineering culture from document-centric to model-based, delivering measurable operational improvements: