An automotive component manufacturer faced a production bottleneck in its induction hardening process due manual loading/ unloading and rapid cycle time. Operators manually loaded and unloaded parts in eight-hour shifts. To address these challenges, the manufacturer sought an automation solution that improved throughput while ensuring workforce safety and operational reliability. However, there were concerns regarding job security, past automation failures, and maintenance complexity.

Our approach involved extensive stakeholder engagement and the creation of a digital twin to simulate and validate automation design before deployment. A SCARA robot was chosen for its precision and speed, and a structured implementation plan was developed, including operator-friendly interventions and maintenance-friendly configurations. The digital twin facilitated preemptive issue resolution, reducing design iterations and optimizing system performance.

The project led to increased efficiency > 20%, improved working conditions, and a scalable automation framework. The structured deployment, combined with extensive digital resources, ensured smooth adoption and post-deployment support.

Key Takeaways 

• This project is a move towards Industry 4.0 and AI in manufacturing capabilities, integrating digital twins and automation to enhance productivity, flexibility, and decision-making.

• Digital twins accelerate automation adoption by allowing stakeholders to visualize, test, and refine solutions before deployment.

• Stakeholder engagement is crucial in overcoming resistance to automation and ensuring alignment with operational needs.

• Preemptive problem-solving through digital simulations reduces costly on-site modifications.

• A structured support plan is necessary post-deployment, as customers require ongoing assistance during the transition period.

• Consider first-year support costs upfront to avoid unanticipated service burdens.

• Factor in additional deployment time due to real-world site challenges and last-minute modifications.

• Automation projects can unlock further digital opportunities, such as automated data capture and performance tracking.

• Several reusable internal and external assets were created providing visibility, scalability, capability and flexibility to the customer and the automation builder. 

An automotive component manufacturer was experiencing a bottleneck in its induction hardening process. The rapid cycle time (a few seconds per part) required one operator per machine to load and unload parts in 8-hour shifts, creating fatigue and strain.

The situation presented an ideal opportunity for automation, yet resistance to change surfaced:

• Concerns over skills and process changes
• Previous negative experiences with automation by the factory team
• Doubts about reliability from production engineering
• Management's requirement for a speedy return on investment (ROI)

Challenges & Stakeholder Concerns 

In any automation project, multiple stakeholders have distinct priorities:

• Management: Increase throughput and improve margins.
• Supervisors: Meet targets, reduce absenteeism and retain skilled labor.
• Maintenance Team: Ensure easy maintenance, calibration, and troubleshooting of new automation.
• Production Engineering: Ensure system reliability and seamless integration.

​​​​2. Our Approach 

We conducted a thorough factory walkthrough and stakeholder interviews, developing a conceptual framework for a robust and efficient automation solution: 

​​​2.1 Solution Design 

• Digital Twin Development: Created a virtual twin framework with simulation to optimize automation design and operations in Autodesk.
• SCARA Robot Selection: Ideal for rapid, precise loading/unloading tasks.
• System Layout Design:

• Frame outlining the induction hardening furnace with defined entry and exit points.
• Fine-tune process to reflect required cycle-time
• Custom-designed pallet system to meet throughput demands.
• Dual-gripper system to load/ unload efficiently.
• Quick pallet swap system on a linear slide for seamless material handling
• Safety structure to prevent operator access during operation.
• Visual notifications for operators to intervene when necessary.

​​​​2.2 Design Review & Stakeholder Buy-In 

Using the digital twin, we collaborated with the customer to:

• Visualize the proposed automation setup.
• Identify necessary shopfloor modifications and utility requirements.
• Share design drawings & BOM and simulation video with subcontract manufacturers
• Determine new skill sets and workforce training needs.
• Update production logging processes.
• Define material flow changes.
• Develop new maintenance and lock-out/tag-out procedures.
• Create training materials for workforce onboarding and upskilling.

​​  2.3 Building the RFP 

To ensure alignment with the customer’s objectives, we:

• Defined required digital assets for implementation, training, and maintenance.
• Created a responsibilities and accountability matrix with formal sign-off processes.
• Established a team for factory acceptance testing, deployment, and sign-off.
• Developed clear acceptance criteria for each implementation stage.
• Identified and confirmed required skill sets for training and ongoing operations.
• Negotiated a milestone-based payment schedule to balance financial planning and deliverables.

​​​2.4 Solution Execution 

• Digital Twin Validation: 

• Eliminated 80% of potential issues before start of build.
• Allowed stakeholders to visualize and accept the automation solution in the context of their shopfloor

• Factory Trials:

• Addressed an unforeseen challenge of component magnetization due to gripper design.
• Integrated preventive maintenance requirements into the robot cycle.
• Optimized robot programming to increase throughput by 10% beyond initial estimates.

​​​2.5 Deployment Learnings 

• Scope creep management is critical—proactive change control is necessary to avoid cost overruns and delays.
• Site readiness is unpredictable; factor in 30% additional time for on-site deployment.
• Customer adoption takes time. Despite providing extensive digital resources, expect ongoing support requests for 45-90 days.
• Incorporate first-year support costs into project pricing to manage post-deployment assistance.

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​​3. Assets Created for Our Internal Use

• Digital Twin Model – Used to validate automation design, optimize layout, and test performance before physical deployment.
• Automation Simulation Data – Collected from digital twin trials to refine robot path optimization and material handling.
• Design and Engineering Documentation – Including:
• Robot integration plans
• Gripper and pallet design specifications
• Safety and positioning guidelines
• Factory Trial Reports – Documenting learnings from prototype testing, including issues like component magnetization.
• Robot Programming & Optimization Scripts – Used for performance enhancements, reducing cycle time, and integrating maintenance schedules.
• Deployment Playbook – Internal process for on-site installation, troubleshooting, and calibration.
• Support & Service Framework – Defining the first-year support model, response protocols, and cost structure.

​​4. Assets Created for Customer Use

Additional Opportunities Identified  for Customer

• Reduced manual touchpoints in adjacent processes.
• Automated capture of testing data for quality assurance.

​​5. Conclusion 

By leveraging a structured approach—incorporating digital twins, stakeholder collaboration, and stage-wise milestones—this robotic automation project delivered:

• Clear communication, deliverables, and positive experience for us and the customer
• Increased production efficiency and reliability
• Improved workplace conditions for operators
• An easily maintainable and scalable automation system

This project not only resolved the immediate production bottleneck but also laid the foundation for further automation initiatives within the factory, enhancing overall manufacturing efficiency.