This article applies Object-Process Methodology (OPM) to model a hand-pour coffee brewing process, illustrating how to distinguish objects, processes, states, enablers, agents, and transformees, and how to link them to requirements and tasks while identifying resource occupancy gaps.
This article demonstrates Mission Engineering principles by using a morning coffee routine to show how to establish a baseline, compare isolated process changes (pre-preparation vs. detailed recording), design a run matrix for experimentation, and define abandonment criteria before investing in new equipment.
This article demonstrates how to translate mission tasks into concrete engineering threads by assigning specific people, tools, and actions to each step, using a coffee-making example to expose resource contention, handoff gaps, and the difference between paper parallelism and real-world feasibility.
This article uses hand-drip coffee as a case study to demonstrate mission engineering task analysis: decomposing tasks, specifying inputs/outputs/start conditions/completion criteria for each step, linking dependencies via quality gates, handling missing items, and distinguishing material independence from resource contention, all while remaining implementation-agnostic.
This article uses a morning coffee scenario to illustrate mission engineering's three-tier metric framework (MOS, MOE, MOP), showing how to define verifiable success criteria, separate stakeholder acceptance from process completion, and create traceable metric definitions that link overall outcomes to specific performance measurements.
This article uses pour-over coffee to illustrate mission engineering's scenario and vignette framework, showing how to define participants, goals, time constraints, starting conditions, verified facts, assumptions, and measurement boundaries so that weekend and rushed weekday mornings can be fairly compared and improved.
This article introduces Mission Engineering through a coffee-making analogy, emphasizing that completing steps doesn't guarantee mission success; it outlines a structured approach using a Mission Description Card to define goals, stakeholders, constraints, and success criteria, and advocates iterative experimentation over rigid processes.
The article argues that an industry AI semantic foundation requires MBSE to define system boundaries and verification loops, OPM to model objects, processes, and state changes, and ontology to consolidate unified semantic assets, providing a five-step implementation path for continuous model-data resonance.
This article argues that successful AI agent deployment depends not on model size but on coordinated digital infrastructure—network, compute, edge, data, and security—citing China's 2026-2028 policy, agent capabilities (context, tools, integration, auditability), dynamic compute placement, data governance, and three maturity criteria: stability, process integration, and compliance.
The article defines six core traits of engineering practice — efficiency, ambiguity, fragility, resilience, maintainability, and safety — each categorized into hard, soft, and chaotic types, illustrated with historical case studies and structured methods for managing them.
From its 2018 construction kickoff to its 2025 commissioning, the Fujian aircraft carrier’s development showcases a timeline of milestones, while the article delves into the critical mathematical models—covering electromagnetic launch, energy storage, fluid dynamics, stability, scheduling, radar, and reliability—that underpin its design and operation.
The article explains MITRE's enterprise engineering approach, describing a comprehensive perspective, enterprise planning and management, technology and infrastructure, information‑intensive systems, systems‑of‑systems, mission‑assurance engineering, transformation planning, and governance, while highlighting the need for adaptable, scalable solutions across large, interdependent organizations.
In this thought‑leading talk, Microsoft China CTO Wei Qing explores how first‑principle thinking, information theory, and cloud‑native architectures can guide organizations through the unknown digital era, emphasizing practical engineering, data integration, and the shift from hype to real‑world technology empowerment.
The article examines the relationship between enterprise architecture and systems engineering, discussing overlapping frameworks such as TOGAF, DoDAF, UPDM, and model‑based approaches, and argues that while they share terminology and goals, EA focuses on business transformation and IT alignment, whereas SE emphasizes technical system development.
The article examines the ongoing debate about whether Enterprise Architecture (EA) is a subset of Systems Engineering (SE), discusses major architecture frameworks such as TOGAF, DoDAF, and UPDM, and highlights the role of model‑based engineering and SysML in bridging EA and SE practices.
