"We Rarely Have Full Data. That’s Why Assumption Discipline Matters."

In the field of engineering—particularly within the oil and gas industry—complete and reliable information is a rare privilege. Engineers are consistently tasked with making critical design and operational decisions based on incomplete data, uncertain boundary conditions, and constantly changing field variables. From variable formation pressures and unstable borehole conditions to inconsistent mud properties and progressive material wear, each factor introduces additional complexity into the design and operational decision-making process. This is further intensified during drilling operations, for instance, where extreme downhole pressures create substantial axial and radial loads; elevated temperatures accelerate material degradation and influence mechanical performance; and high-frequency vibrations and intermittent shock loads caused by bit-rock interaction, pipe movement, and tool dynamics—generate complex, nonlinear stress conditions. Engineers must approach these shifting conditions as standard features of the operating environment. In this reality, uncertainty is not a deviation—it is a defining characteristic of the system. Effective engineering demands forward-thinking strategies, resilient design frameworks, and disciplined assumption management from the outset.

To move forward under such conditions, engineers must not rely on guesses, nor freeze waiting for perfect clarity. Instead, they must adopt a disciplined, structured strategy for dealing with the unknowns.

Strategic Planning for Engineering Under Uncertainty:

Engineering under uncertainty is not improvisation—it is structured foresight. The strategic plan begins with acknowledgment: some data will always be missing, some properties will always vary in the field, and some interactions will always evolve over time. Therefore, systems must be designed to adapt, absorb, and recover, not just perform in ideal lab conditions.

This mindset drives both the engineering planning and the design methodology.

Core Engineering Pillars for Assumption Management

1. Confidence Mapping of Assumptions:
Each assumption is classified based on its source and reliability. Field-tested data, empirical rules, simulations, and vendor specifications all carry different levels of confidence. This classification informs where to apply design margins, where to focus testing, and where risk must be managed more actively.

Design Principle: An untracked assumption is a silent liability. Confidence mapping makes uncertainty visible, measurable, and actionable.

2. Boundary-Based Design Thinking
Instead of designing around the nominal case, engineers define the limits: thermal boundaries, load extremes, material degradation, or operational fluctuations. The system is then tested, modeled, and designed to survive at or near those boundaries.

Design Principle: The real world lives in the gray zones. Engineering must anticipate the edges, not just the averages.

3. Graceful Degradation Planning
All systems eventually reach performance limits. Instead of brittle failure, robust systems degrade in stages maintaining partial function, triggering warnings, or switching to fallback modes.

Design Principle: A system prepared to fail gently performs longer and recovers faster.

4. Integrated Assumption Logs in Design Reviews
Every major design review includes a dedicated section for assumptions. This includes what was assumed, why, how it was justified, and how it could fail. Assumptions are tracked like critical components, and reviewed across disciplines.

Design Principle: When assumptions are treated with the same rigor as parts and drawings, design strength becomes holistic.

5. Field Feedback Loops
Designs must be connected to reality. Real-world deviations from assumptions—such as higher vibration, lower-than-expected flow efficiency, or unexpected temperature or loadings spikes—must be documented, analyzed, and fed back into the design process.

Design Principle: Field data is not just validation; it’s the sharpening stone for the next generation of designs.

6. Simulation for Uncertainty Zones
In cases where testing is impractical, simulations are used to study wide uncertainty zones. Monte Carlo analysis, sensitivity studies, and parametric sweeps allow engineers to explore how systems behave under diverse scenarios.

Design Principle: Simulations are not to predict exact numbers—they are to reveal system behavior across uncertainty.

7. Design Margin by Uncertainty Priority
Design margins are not distributed equally. Margins are increased where assumption confidence is low or where the cost of failure is high. This is a targeted investment—not over-engineering, but risk-weighted robustness.

Design Principle: Not all margins are equal; margin is a currency spent where it buys resilience.

Engineering Mindset: Moving from Certainty-Seeking to Resilience-Building

The goal is not to remove uncertainty. The goal is to engineer through it. Strategic design planning in uncertain environments begins with recognizing what is unknown, quantifying what can be estimated, and building a system that tolerates, adapts to, and learns from deviation.

Uncertainty is not an exception—it is a permanent design condition. And engineering must evolve accordingly.

Strong design emerges not from perfection, but from preparedness:

• Prepared for variability.
• Prepared for blind spots.
• Prepared to operate beyond the edges of the known.

In engineering, more is not always better. While we often take pride in crafting robust, high-performance systems, there’s a fine line between engineering excellence and unnecessary complexity. Over-engineering by adding more than what is truly needed is rarely a sign of technical strength; it’s often a reflection of unclear priorities, lack of confidence in the requirements and symptom of uncertainty, or an absence of disciplined design thinking. What may feel safe or look impressive can quietly erode value by increasing costs, delaying time to market, and burdening maintenance efforts, all without delivering proportional benefit to the customer or the business. Over-Engineering is not just a technical inefficiency; it’s a strategic liability and business risk that undermines agility, profitability, and innovation.

Here’s how it silently erodes business value:

• Energy inefficiency: Designs drift away from their optimal operational window, consuming more than necessary.
• Serviceability decline: More components, more interfaces, and tighter tolerances lead to harder maintenance, longer downtimes as Mean Time to Repair (MTTR) rises and field troubleshooting becomes more difficult. Thus, service reliability suffers.
• Decreased system reliability: Ironically, trying to make something “more robust” by adding layers of redundancy or complexity often reduces reliability even when parts are individually robust. More interfaces, interdependencies, and failure points create more potential failure modes, not fewer.
• Wasted engineering capacity: When teams are absorbed in designing, testing, and validating what’s unnecessary, they lose time for real innovation. Engineering bandwidth is finite. Over-engineering consumes attention that could be spent solving high-value problems rather than spending the time perfecting low-risk areas. 
• Slow innovation (Slower Design Cycle): More features and tighter tolerances mean longer verification loops, more exhaustive simulations, further needing for test benches, and bloated documentation. The result is stalled progress and speed-to-market suffers — and with that, competitiveness.
• Roadmap Paralysis (Legacy friction): Over-engineered legacy systems create inertia to evolve. When something is overbuilt, it becomes harder to scale, adapt, or integrate into new technology roadmaps. Engineers hesitate to make changes. The project teams are constrained by the weight of their own designs. Technical debt accrues silently. 

Why Does Over-Engineering Happen?

Understanding root causes is essential. It usually starts with good intentions, but grows from common habits:

• Poor Requirement Definition: Ambiguous, overgeneralized, or inflated requirements lead engineers to “cover all bases.” Without clear constraints, scope naturally expands. This leads us to “play it safe” by adding more! Clear, focused problem definition is essential here to avoid chasing complexity instead of delivering fit-for-purpose value.
• Design by Fear: Trying to cover every possible case, instead of focusing on the most likely; as in the absence of strong validation tools or organizational confidence, engineers compensate that by adding more — more strength, more margin, more redundancy — rather than trusting sound analysis.
• No Clear Definition of "Good Enough": Without a clear definition of “good enough”, design efforts can spiral endlessly in search of perfection. Engineers may continue refining features, tolerances, or performance far beyond what’s necessary for success. This lack of stopping criteria wastes time, delays delivery, and often adds complexity without proportional benefit.
• Disconnected Decision-Making: When teams focus only on technical metrics without understanding cost, market fit, or lifecycle value, decisions lack business context. I call this as "Design in Isolation".
• Mistaking Over-Engineering for Quality: Over-engineering is often mistaken for high quality — as if adding complexity, features, or tighter tolerances automatically means better performance or safer outcomes. In reality, these excesses often introduce inefficiencies, higher costs, and new failure risks without delivering meaningful value.

In short, over-engineering often means we’re thinking too much without asking the right questions; we should be asking: 

•  What is the core problem we're solving?  
• What are the minimum performance requirements for success? 
• What will this design cost—not just to build, but to operate, maintain, and evolve? 
• Are we protecting against real risks, or just responding to fear or habit? 
• Where is the point of diminishing returns? 
• Is this feature solving a verified need, or just adding theoretical robustness? 
• Can this be simplified without compromising safety or function? 
• And most importantly, who will build it, use it, and maintain it—and what do they truly need?

These questions guide us toward purposeful, efficient design that serves both the engineering mission and the business outcome.

How Do We Prevent It?

Overcoming over-engineering requires a cultural and strategic shift. We must instill in our teams the right mindset, backed by discipline and confidence (We need to remember that strong engineering is all about "Smart-Choosing"):

We need:

• First-Principles Thinking: Strip away assumptions. Start with what physics, economics, and user needs truly demand. Design begins with a question, not a solution.
• Analytical Confidence: Equip teams with the tools and skills to quantify risk, margin, and performance. A confident engineer doesn't overcompensate, he optimizes.
• Design Excellence Lies in Balance: Chasing the “best” in every thing often leads to bloated, over-engineered solutions that miss the bigger picture. True engineering value comes from balancing performance, cost, and reliability to meet the real-world use case, no more, no less. Excellence is about delivering just enough to meet the goal with precision, efficiency, and purpose.
• Commercial Awareness: Engineering is not just a technical exercise. It’s a value-delivery function. Every design decision should reflect a balance of cost, performance, manufacturability, serviceability, and lifecycle ROI.
• Design Discipline: Minimalism is not weakness, it’s wisdom. Leadership means being able to say, “This is enough,” based on evidence, not emotion. The key is to set a clear definition of "fit-for-purpose" and stick to it.
• Strategic Alignment: Tie every engineering effort to business value and strategy. If the design does not serve the market, support the roadmap, or improve profitability, it needs to be reconsidered. That is why value simple and effective solutions.

A product’s excellence come from how precisely and purposefully it solves a defined problem. As engineering leaders, our value is in how effectively we balance technical need, business risk, and long-term value. Engineering is fundamentally a discipline of trade-offs —not a pursuit of perfection— and the most impactful designs aren’t just functional; they are aligned with the business they serve. To lead with intent means designing with clarity, delivering with focus, and resisting the urge to build more when building smart is enough. It’s time we return to purpose-driven design, where every decision counts, and value is the true benchmark of engineering excellence.

Avoiding an undercut with a standard gear (standard pressure angle of 20°) requires a minimum number of teeth of 17. If gears are nevertheless to be manufactured below the limit number of teeth (e.g. because a certain transmission ratio is to be achieved), the undercut must be avoided in another way. For this purpose, a so-called profile shift can be used.

With a profile shift, the tool profile is shifted outwards by a certain amount during gear cutting. The animation below shows the effects of a profile shift on the tooth form of a gear with 8 teeth. It becomes clear that as the profile shift increases, the undercut becomes smaller and can even be completely avoided.

Even if the tooth shapes differ from each other, the teeth can still mesh with each other. Profile shifted gears (also called corrected gears) can therefore be easily paired with non-profile shifted gears (so-called standard gears) as long as they are manufactured with the same tool and therefore have the same module.

Even if this may not seem so at first glance, a profile shift has no influence on the shape of the tooth flank itself. All profile shifted gears use the same involute for the tooth shape compared to their corresponding standard gears. Only another part of the same involute is used. This becomes clear when the tooth flanks of the gears with different profile shifts are placed on top of each other.
Note that the base circle for constructing the involute is determined solely by the flank angle of the tool profile (standard pressure angle) during gear cutting. And since the angle of the cutting edges does not change with a profile shift, the base circle and thus the involute do not change either.

The radius of curvature of the involute increases with increasing length, i.e. the further away the involute is from the base circle, the larger the radius of curvature is and the less strongly it is therefore curved. The flank shape at this more distant area is rather “flat” than “pointed”. The smaller curvature leads to a larger contact surface of the flanks, which reduces the pressure accordingly (less Hertzian contact stress). This reduces the stress on the flanks and thus increases the flank load-bearing capacity.

The animation below shows the profile shift of a gear with 6 teeth to avoid an undercut. In this case, the thickness of the tip tooth even decreases so much that the involutes taper before the shifted tip diameter is reached. The increase of the tip circle radius by the amount of the profile shift cannot therefore be maintained in this case, the tip diameter is inevitably shortened.

In addition, the tip circle would have to be shortened again to at least 0.2 times the module in order to increase the thickness of the tip tooth. However, such a large reduction of the tip circle would also result in a correspondingly large reduction of the line of action. Involute gears with fewer than 7 teeth should therefore be avoided by any means.

With corrected gears, an extended part of the involute is used as tooth flank compared to standard gears. When meshing with another gear, this further curved part of the involute requires the center distance to be increased by the amount of the profile shift V= x⋅m.

In summary, it can be stated that a profile shift is always applied if:
​

• An undercut is be avoided,
• The tooth strength must be increased,
• The surface pressure at the flanks is to be decreased, or
• The center distance must be adjusted.

Traditionally it has been very difficult to weld together dissimilar materials like glass and metal due to their different thermal properties as the high temperatures and highly different thermal expansions involved cause the glass to shatter.
 
Currently, glass and metal are often held together with adhesives, but that process is messy, and parts can gradually move out of place. Additionally, “organic chemicals from the adhesive can be gradually released and can lead to reduced product lifetime
 
Instead of adhesives, the method Hand and his research team from Heriot-Watt university used to join glass and metal is a technique of recent interest called ultrafast laser micro-welding. Ultrafast laser micro-welding involves aiming laser pulses at the interface between two materials in quick succession so that heat accumulates at the interface and leads to localized melting. When the laser pulses stop and the material re-solidifies, strong and robust bonds form between the materials along the interface.
So far, the majority of research on ultrafast laser micro-welding has focused on similar or slightly dissimilar materials, while research on highly dissimilar materials has concentrated on bonding glass and silicon.

For research on glass and metal welding, Hand and his team explain these previous studies were limited to proof-of-principle demonstrations involving specific material combinations and limited systematic studies. That is why the researchers “aim to move ultrafast micro-welding closer to an industrially viable technique through a systematic study of the parameter space for welding and demonstrating accelerated lifetime survivability,” as they explain in their paper.

However, due to the brittle nature of glass, creating enough samples to produce statistically relevant tests of all parameters was impractical—each process parameter set would require at least 20 samples! So, the researchers chose to focus only on pulse energy and focal plane for this study.
Even just focusing on pulse energy and focal plane, though, would require more than 1,000 individual welds. To limit the number of required samples, the researchers carried out two tests for each pair of parameters to create a parameter map. They used the map to identify regions of interest to run full, 20-sample tests. After running these tests, they identified an “optimized” set of parameters for accelerated lifetime testing.

While the Heriot-Watt press release states various optical materials like quartz, borosilicate glass, and sapphire were all successfully welded to metals like aluminum, titanium, and stainless steel, the actual paper focuses on welding two specific glasses [Spectrosil 2000 (SiO2) and Schott N-BK7 (BK7)] to 6082 aluminum alloy (Al6082).

When discussing the results, one somewhat counter intuitive finding the researchers highlight is that minor cracking around the melt volume (particularly in the glass) indicates a good weld. Cracking is due to the significant difference in thermal expansion between glass and metal—through cracking, glass relieves itself of the thermal stress that occurs during cooling. “[This cracking] does not indicate a reduction in the weld strength,” the authors stress.

In the future, the authors note that further work in thermal compensation, either through interlayers or surface patterning to relieve thermal stress, is needed to develop a reliable welding process, “particularly for material combinations with a large mismatch of thermal expansion, e.g., Al6082–SiO2.”

Auxetic materials are a class of meta-materials which exhibit negative Poisson’s Ratio (Meta-materials are a class of man-made materials that have been specially and artificially engineered to contain small inhomogeneities which alter the properties on a macroscopic level). They have been known for over a hundred years but have only gained attention in recent decades. They can be single molecules, but more often they consist of an engineered material with a particular structure on the macroscopic level. Auxetic materials can occur in nature, but they are very rare. For example, some rocks and minerals demonstrate auxetic properties as does the skin on a cow’s teats.

Auxetics are created by modifying the macrostructure of the material so that it contains hinge-like features which change shape when a force is applied. If a tensile force is applied the hinge-like structures extend, thus causing lateral expansion. If a compressive force is applied the hinge-like structures fold even further causing lateral contraction.

A common analogy used to describe the behavior of auxetic materials is to consider an elastic cord with an inelastic string wrapped around it. When a tensile force is applied the inelastic material straightens at the same time as the elastic cord stretches, thus effectively increasing the volume of the structure.
Auxetic materials are often based on foam structures and as such they have a relatively low density. It is this open cell structure which can be modified to give the desired properties.

The unusual properties of auxetic materials mean that they are relatively resistant to denting. When an auxetic is hit the compression caused by the impact results in the material compressing towards the point of the impact, thus becoming much denser and resisting the force. Auxetic materials are also more resistant to fracture; they expand laterally as a force is applied and this closes up potential cracks in the material before they start to grow. The main drawback of these materials is that they are often too porous, not dense enough or not stiff enough for load bearing applications and when these properties are adjusted the auxetic behavior tends to be reduced. Applications of these materials therefore often rely on a compromise of properties.

Auxetic materials can essentially be made in two different ways. In the top-down approach everyday polymers are manipulated to give the desired structure and properties. In the bottom-up approach the material is built up from scratch, molecule by molecule, allowing them to be engineered on a very small scale. In both cases the objective is to create a repeating pattern of building blocks or cells which contain the necessary hinge-like features.

There have been many suggested uses for auxetic materials, but most of these have yet to come to fruition commercially. These materials can be difficult to process on a large scale, making industrial manufacture difficult. Some potential areas for use are described below:

Biomedical applications
Many of the materials that are currently used in medical applications can be processed to exhibit auxetic properties. It has been suggested that auxetic materials could be used to dilate blood vessels during heart surgery. A piece of auxetic foam, possibly made from PTFE would be inserted into the blood vessel and then tension applied to this to cause lateral expansion and open out the vessel. Auxetics could also be used in surgical implants and prosthesis and for the anchors used to hold sutures, muscles and ligaments in place.

Filters
Traditional filters can be incredibly difficult to clean, leading to them being thrown away prematurely. A filter made from an auxetic foam could be cleaned much more easily by simply applying a tensile force to open up the pores. Once clean the force can be removed and the filter refitted.

Auxetic fibers
This is one area which does show real potential for exploitation. The key here is the development of a continuous process for developing auxetic materials in the form of fibers. The resulting fibers could be used in monofilament or multifilament form and could be knitted or woven together to make cloth. It has been suggested that these fabrics could be used in crash helmets, body armor and sports clothing where their dent and fracture resistance would be exploited.

Auxetic materials could also be added to metallic materials such as steels to create composites with improved resistance to cracking under shear strain (twisting).