Skip to content
MarketScale
‹ Back to IndustriesSciences

Metrology Matters: 2D and 3D Surface Parameters – Should You Stick to the Typical Results?

The episode of Metrology Matters discusses insights on 2D and 3D surface parameter measurements with experts Dr. Mark Mulberg and Carl Musolff. It highlights the importance of these parameters in design and metrology.

This story was produced through MarketScale. See how Sciences teams put it to work with Executive Thought Leadership.

By Sciences · Digital MetrologyMeasureMetrologyMetrology Matters
Share

Key takeaways

01

Experts provide insights on 2D and 3D surface parameter measurements.

02

Designers use various surface texture parameters for accuracy.

03

Metrology expertise is crucial for optimized measurements.

This episode of Metrology Matters features two bona fide experts in the field in Digital Metrology’s Dr. Mark Mulberg and Musolff Consulting’s Carl Musolff – and they’ve got front-line insights to share about getting the most out of 2D and 3D surface parameter measurements.

Currently, designers and companies specify surface texture parameters in a multitude of ways, though a common method is to leverage older, similar designs and modify as necessary based on more demanding environments, etc. However, this is often an inexact science – and a headache-inducing one.

Though the most expensive option, testing is the most accurate method for determining what works and what doesn’t. Measuring a part, putting it through rigors similar to what it will actually undergo on the job, and measuring again is really the only surefire way to get the clearest picture of its performance.

Another key consideration that Malburg said is often overlooked is waviness – in fact, he said a colleague calls it “the hidden killer.”

The trio continued to explore best practices and innovations in surface metrology, diving into why the shape of a surface is more important than its roughness, the importance of interacting with a surface and learning how its shape can impact its function, and why appreciating a surface visually helps you appreciate and understand its many critical attributes.

Follow us on social media for the latest updates in B2B!

Twitter – @MarketScale

Facebook – facebook.com/marketscale

LinkedIn – linkedin.com/company/marketscale

About the author

S
Sciences

Sciences: are you visible to AI?

Before they reach out, Sciences buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one expert. Imagine publishing your whole team.

This article was produced through MarketScale. Create a free workspace and turn your own team's expertise into articles, video, and social posts. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Sciences Insights

Biopharma's $300 Billion Problem Is Driving the Biggest M&A Cycle in a Decade

Biopharma's $300 Billion Problem Is Driving the Biggest M&A Cycle in a Decade

The pharmaceutical industry is facing a significant challenge as over $300 billion in branded pharmaceutical revenue is set to lose patent protection by 2030. This revenue gap is driving the largest merger and acquisition cycle seen in a decade, with companies seeking external growth through acquisitions. This shift is impacting the entire life sciences supply chain, prompting strategic changes across the industry.

  • 01Over $300 billion in pharmaceutical revenue is at risk due to patent expirations by 2030.
  • 02Big Pharma is engaging in an aggressive cycle of mergers and acquisitions.
  • 03The acquisitions are reshaping the life sciences supply chain.

Jun 29, 2026

Quotient Sciences launches Phase I study of what it calls the first AI-formulated drug in the clinic

Quotient Sciences launches Phase I study of what it calls the first AI-formulated drug in the clinic

Quotient Sciences has initiated a Phase I clinical study at its UK facility for an oral solid dose formulation designed using artificial intelligence — what the company believes is the first AI-formulated drug to reach human clinical evaluation. The study, cleared by the UK's Medicines and Healthcare products Regulatory Agency, will assess safety and pharmacokinetics in healthy volunteers. The program, which used Intrepid Labs' machine learning algorithm, signals a broader shift in how contract drug development organizations are integrating AI across formulation and clinical workflows.

  • 01Quotient Sciences initiated a Phase I study of an AI-designed oral solid dose formulation at its UK facility following MHRA approval — the first such case the company believes has been reported.
  • 02The formulation was developed using Intrepid Labs' advanced machine learning algorithm in combination with Quotient Sciences' Translational Pharmaceutics platform.
  • 03The milestone is part of a broader CRDMO strategy to embed AI-enabled approaches across formulation development and clinical workflows, with implications for the wider contract pharma sector.

Jun 17, 2026

Quotient Sciences launches Phase I trial of what it calls the first AI-formulated drug to reach the clinic

Quotient Sciences launches Phase I trial of what it calls the first AI-formulated drug to reach the clinic

Quotient Sciences has initiated a Phase I clinical study of an oral solid dose formulation designed using AI, cleared by the UK's MHRA and conducted at the company's UK facility. The trial—built on machine learning algorithms from partner Intrepid Labs and Quotient's Translational Pharmaceutics platform—aims to validate AI as a direct contributor to formulation design rather than just an upstream analytical tool. Benchling characterizes the broader moment as biotech entering a "builder phase," in which leading organizations embed AI capability at the bench level rather than running isolated pilots.

  • 01Quotient Sciences has dosed healthy volunteers in a Phase I study it describes as the first clinical evaluation of an AI-designed oral formulation, following approval from the UK's MHRA.
  • 02The formulation was developed using advanced machine learning algorithms from Intrepid Labs, integrated with Quotient Sciences' Translational Pharmaceutics platform.
  • 03Benchling identifies a sector-wide shift toward embedding AI capability directly at the bench, moving beyond isolated pilots to structural adoption across biotech R&D.

Jun 17, 2026

Explore More Sciences Insights

Read more expert perspectives from across Sciences.

Browse Sciences Hub

About the Experts

S
Sciences
DM
Dr. Mark Mulberg

Expert

Digital Metrology

CM
Carl Musolff

Consultant

Musolff Consulting