Using of AI to enhance efficiency in biochemical plant design

How kasel group uses AI to enhance efficiency in biochemical plant design

At kasel group, we are increasingly integrating Artificial Intelligence (AI) into our detailed engineering workflows. This approach allows us to reduce project timelines, cut costs, and improve precision in every phase of plant design.

Why are we doing this?

AI empowers our engineers to focus on value-driven tasks while automating repetitive, time-consuming work. Below are the key areas where AI is already making a significant impact:

1. Process Simulation & Optimization

AI-driven models can complement or replace time-consuming simulations (e.g., CFD, ASPEN).
AI helps optimize:

• Yield, titer, and productivity
• Energy and water consumption
• Reactor and downstream conditions

Result: Faster iteration and smarter early-stage decisions.

2. Equipment Sizing & Selection

• ML models predict equipment specs (e.g., fermenter size, heat exchangers).
• Generative tools suggest optimal layouts to reduce cost and footprint.

Result: Reduced manual sizing cycles and improved layout efficiency.

3. Fermentation Process Modeling

AI captures complex fermentation kinetics using historical/experimental data.
Optimizations include:

• Feed strategies (batch, fed-batch, continuous)
• Aeration, agitation, pH & nutrient control

Result: Better process models and fewer pilot trials.

4. Documentation & Compliance Automation

Natural Language Processing (NLP) tools help:

• Extract regulatory info (GMP, FDA, EMA)
• Auto-generate SOPs, HAZOPs, and EHS reports

Result: Saves engineering hours spent on paperwork and validation.

5. 3D Facility Layout & Clash Detection

AI-powered design tools support:

• Optimal spatial planning for safety and maintenance
• BIM integration and clash resolution with digital twins

Result: Shorter layout cycles and safer designs.

6. Piping Design & Sterile Piping Automation

a. Automated Piping Layout

• Auto-generates 3D piping from PFDs
• Ensures code compliance (ASME, ISO)

b. Clash Detection & Rerouting

• AI detects and resolves routing clashes early

c. Design Rule Checking (DRC)

• Validates pressure ratings, slopes, support spacing

d. Material Take-Off (MTO) & BOM

• Auto-generates MTO/BOM from P&IDs

e. BIM/Digital Twin Integration

• Predictive analytics for future stress or fatigue

f. Generative Design

• Proposes multiple GMP-compliant piping layouts

g. Sterile Constraints Routing

• Auto-applies rules: drain slope, dead leg avoidance, orbital welds

h. CIP/SIP Validation

• Verifies sterilization coverage and time–temperature profiles

i. Component Suggestion & Standardization

• Recommends valves, instruments, and tube specs

j. Clash & Clean Zone Checks

• Detects clean zone violations, optimizes aseptic access

Result: Shorter design cycles, built-in compliance, and cleaner execution.

7. Electrical & Control System Design

a. Auto-Generated Wiring Diagrams

b. Smart Instrumentation & Loop Diagrams

c. Control Logic Development

d. IO Lists & Control Panel Design

e. Control System Simulation

Result: Faster, more accurate control design and early testing.

8. Compliance Checking & Safety Automation

AI checks compliance with standards like:

• IEC 61511, NFPA 79, UL508A
• SIL requirements and ATEX classifications

Result: Fewer manual reviews and faster regulatory readiness.

The kasel advantage

By applying AI across every stage of detailed design—from simulation and layout to automation and documentation—we deliver faster, smarter, and more cost-effective engineering solutions.
AI doesn’t replace engineers. It enhances them. At kasel group , we believe the future of engineering is intelligent—and it’s already here.