Writing Effective Problem Statements

The way you describe your engineering problem directly affects the quality of your research. Here's how to get better results.

What Makes a Good Problem Statement

Strong problem statements share these characteristics:

1. Quantified Details

Include specific numbers, measurements, and requirements.

• Cycles per year: ~2 million
• Temperature range: -20°C to 45°C
• Power requirement: 50W
• Weight limit: under 200g
• Precision needed: ±0.5mm

2. Clear Constraints

State what you can't do, not just what you need.

• "Can't use fans (dust/reliability concerns)"
• "Titanium is too expensive"
• "Must be sealed — no active cooling"
• "Weight-sensitive application"

3. Context About What You've Tried

Help Sparlo focus on new directions by mentioning what hasn't worked.

• "Current passive heatsink isn't cutting it"
• "Current steel design is failing at 18 months"
• "Passive isolators I've tried either don't isolate enough or are too soft"

4. Cross-Industry Thinking

Ask explicitly for approaches from other industries — this is where the best insights often come from.

• "What approaches from other marine industries could help?"
• "How do other industries handle high-cycle fatigue?"
• "What mechanical or thermal approaches from other industries could step-change this?"

Example Problem Statements

These real examples show what effective problem statements look like:

Thermal Management

"I need to dissipate 50W of heat from a sealed electronics enclosure in an outdoor environment. Can't use fans (dust/reliability), can't add significant mass (drone application), ambient temps up to 45°C. Current passive heatsink isn't cutting it."

Why it works: Clear power requirement, explicit constraints (no fans, weight-sensitive, sealed), environmental context, current solution baseline.

Energy & Scale

"Reverse osmosis desalination is stuck at ~3-4 kWh per cubic meter — we're approaching thermodynamic limits with membrane tech. What mechanical or thermal approaches from other industries could step-change this? Looking for concepts that could work at municipal scale (100,000+ m³/day)."

Why it works: Quantified current state, identifies the limitation (thermodynamic limits), explicit request for cross-industry approaches, scale requirements defined.

Access & Operations

"Offshore wind turbines need maintenance but we can only access them ~60% of days due to wave height limits on crew transfer vessels. This drives up O&M costs and reduces availability. The industry is stuck between expensive solutions (helicopters, walk-to-work vessels) and accepting weather downtime. What motion compensation or access system approaches from other marine industries could expand our weather window cost-effectively?"

Why it works: Clear problem quantification (60% access), economic impact explained, existing solutions acknowledged with limitations, specific technical direction (motion compensation).

Materials & Fatigue

"We have a linkage mechanism in a prosthetic knee joint that sees ~2 million cycles per year with highly variable loading (walking, stairs, sitting). Current steel design is failing at 18 months. Titanium is too expensive. How do other industries handle high-cycle fatigue in compact, weight-sensitive applications?"

Why it works: Specific cycle count, failure timeline, material constraints (cost), asks for cross-industry solutions, clear design constraints (compact, weight-sensitive).

Precision & Vibration

"Mounting a sensitive optical sensor on an agricultural robot. Need to isolate it from chassis vibration (5-50 Hz) but it also needs to stay precisely positioned (±0.5mm) relative to the camera boom. Passive isolators I've tried either don't isolate enough or are too soft for the positioning requirement."

Why it works: Specific frequency range, precision requirement quantified, describes the tradeoff problem, mentions what's been tried.

Detection Indicators

As you type your problem, you'll see three indicators light up:

• Problem — Sparlo has detected your core challenge
• Constraints — Limitations and requirements identified
• Success Criteria — What success looks like is clear

If an indicator doesn't light up, try adding more detail in that area.

Common Mistakes

Too Vague

"We need better performance" — Better at what? Under what conditions? With what constraints?

Missing Constraints

"We need a faster motor" — What's the size limit? Power budget? Cost target? Environment?

No Context

"Our pump is failing" — How is it failing? After how long? Under what conditions? What have you tried?

Solution-Focused

"We need a titanium part" — You've already decided on the solution. Instead, describe the problem that made you think of titanium, and let Sparlo explore alternatives.

What's Next

• File Attachments - Add supporting documents
• The Generation Process - What happens during research