Science and technology are entering an era where speed of discovery and efficient output matter as much as experimental quality. Yet too many research and testing laboratories are physically designed like traditional offices — tuned to appearance rather than workflow, throughput, or operational efficiency. In contrast, industries that embraced manufacturing excellence decades ago — aerospace, automotive, electronics, and pharmaceuticals — have moved beyond office centric layouts to production oriented facilities designed for flow, safety, standardisation, and continuous throughput.
The result? Laboratories that struggle with bottlenecks, inconsistent outcomes, and wasted human effort. Next generation labs — whether autonomous facilities, cloud laboratories, or lean driven QC labs — embody factory principles: they minimise waste, prioritise flow, harness automation, and deliver predictable, reproducible, and scalable output.
This article explains why labs should think like factories — but often don’t — and illustrates how industry innovators are shifting the paradigm.
1. The Misalignment: Lab Design vs. Operational Reality
Traditionally, many labs are laid out like office suites, with bench spaces scattered, workstations isolated, utility lines routed inefficiently, and circulation more suited to conversation than workflow. This reflects a legacy design mindset where research was craft like, serendipitous, and individualistic.
Yet modern science is data driven, process heavy, and throughput sensitive. A poorly designed lab can hinder performance in multiple ways:
In manufacturing, these inefficiencies would be unacceptable because factories are optimised for predictable and fast throughput. Labs should adopt that same discipline — because experiments are often just specialised production steps.
2. What Manufacturing Principles Bring to Laboratories
Several structured methodologies from manufacturing — such as Lean, Six Sigma, and Factory Physics — can be translated into laboratory design to enhance throughput without compromising quality.
a) Lean Principles and Waste Elimination
Lean, born from the Toyota Production System, focuses on creating flow, eliminating waste, and delivering value. In lab contexts, Lean means:
Studies show applying Lean reduces turnaround times in diagnostic labs and simplifies steps, improving both speed and reliability of outputs.
b) Modular and Flexible Workcells
Manufacturing increasingly uses modular workcell design: discrete modules that can be scaled and rearranged. The same idea works in labs — modular benches, mobile utilities, and configurable services allow workflows to evolve as research needs change.
c) Information Flow and Digital Twins
Factories today use digital models (digital twins) to simulate workflows, analyse bottlenecks, and predict impacts of layout changes. Emerging lab design trends incorporate digital models and simulation to prevalidate layouts and airflow, reducing risk and improving utility provision.
3. Case Studies: Labs That Think Like Factories
a) Cloud Laboratories — The Ultimate Factory Analogy
Cloud labs like Emerald Cloud Lab are perhaps the clearest real world example of laboratory as factory. These facilities:
- Operate 24/7 with robotic instrumentscontrolled remotely via software.
- Provide scientists with programmable experiment execution.
- Standardise experimental conditions and data capture, increasing reproducibility.
- Abstract scientists from the physical lab, making “execution” a service rather than a physical act.
Emerald Cloud Lab in particular houses hundreds of automated instruments that execute protocols with minimal human intervention, delivering large quantities of experimental data with consistent quality and reproducibility.
Why it works: Just like an automated production line, cloud labs are engineered for throughput, repeatability, and quality control.
b) Lean QC Labs in Pharma
Pharmaceutical quality control (QC) labs are another successful example of manufacturing principles at work. Novartis Vaccines Division’s Lean Lab Program systematically applied Lean during lab design and operation, focusing on 5S organisation, visual controls, and flow optimisation. Their experience confirmed that lab layout directly affects process behaviours, communications, and waste generation.
Similarly, clinical diagnostic labs that apply Lean methods have demonstrated measurable improvements in test delivery times.
4. Why Traditional Lab Design Fails Production Logic
a) Emphasis on Human Comfort Over Workflow
Office centric design privileges aesthetics, sightlines, and “collaboration zones,” often at the expense of logical sample and material progression. While human comfort matters, workflow sequencing should be the design starting point.
b) Siloed Engineering Decisions
Facility engineers and architects frequently design labs independently of operational experts. In manufacturing, engineers and operators co design facilities; in labs, those insights too often come too late.
c) Legacy Regulation Bias
Laboratory design is understandably conservative about safety, ventilation, and containment. However, strict adherence to outdated standards can inadvertently create workflow barriers. Integrated design that unifies safety with flow maximisation is needed.
5. Design Principles for FactoryLike Laboratories
To transform labs from office lookalikes to production engines, adopt the following design principles:
a) WorkflowFirst Layouts
Map core processes — from sample intake to final data capture — before placing furniture or utilities. Position instruments and utilities along logical sequences to reduce travel distances.
Design tip: Use value stream mapping early in the planning process to visualise and optimise workflows.
b) Modular and Reconfigurable Infrastructure
Install modular benches, service panels, and flexible power/data delivery systems. This supports changing research needs and supports future proofing.
c) AutomationReady Spaces
Allocate space and connectivity for robotics, sample handlers, and IoT devices. Provide robust network infrastructure and spare utilities to accelerate integration of automation systems.
d) Safety and Efficiency HandinHand
Lab ventilation, safety stations, and emergency exits should be placed such that they support flow and reduce stoppages, not only meet compliance minimally.
e) Data and Control Infrastructure
Deploy lab information management systems (LIMS), electronic lab notebooks (ELN), and real time monitoring as foundational elements — just as manufacturing uses MES/ERP systems.
6. Measuring Success: KPIs for Efficient Labs
To quantify improvement after redesign or optimisation, track:
- Turnaround time for common tasks (e.g., PCR runs, analysis reports).
- Instrument utilisation rates (idle time vs processing time).
- Sample throughput per technician per shift.
- Error/rework rates linked to workflow and layout frustration.
- Overall equipment effectiveness (OEE) analogues tailored to lab tasks.
These KPIs allow lab managers to measure whether changes deliver measurable productivity gains.
7. Challenges and Change Management
Transforming lab design culture is not trivial. Common barriers include:
- Cultural resistance: Scientists often prize autonomy over standardised workflows.
- Budget pressures: Upfront costs for automation and infrastructure upgrades can be substantial.
- Regulatory constraints: Safety codes, HVAC needs, and hazardous materials handling demand careful engineering.
Effective transformation requires cross functional leadership, measurable objectives, and incremental implementation to prove return on investment.