Interior Design, Packaging & Ergonomics
About us Interior Design, Packaging & Ergonomics
The Certificate Program/Comprehensive Program in Product and Experience Engineering provides a solid foundation applicable to multiple domains (exterior/interior, HMI/UX, Class A surfaces, materials and sustainability, lighting, acoustics, haptics, and technical documentation with AI). The program integrates user-centered design, modeling and simulation, physical/digital prototyping, and lifecycle management (PLM/PDM), connecting conception, validation, and manufacturing to accelerate decision-making and ensure regulatory compliance.
The approach combines technical rigor and business criteria to deliver efficient, safe, and scalable solutions: from requirements definition and ergonomics to change traceability, testing, and certification. Upon completion, you will be able to lead end-to-end design and validation processes, integrate advanced tools (VR/AR, RAG/NLP, CAD/CAM), and coordinate multidisciplinary teams in high-demand environments.
Target keywords (natural in the text): user-centered design, Class A surfaces, HMI/UX, PLM/PDM, simulation, prototyping, sustainability, lighting, acoustics, haptics, regulations, AI/NLP, RAG.
Interior Design, Packaging & Ergonomics
- Format: Online
- Duration: 19 months
- Time: 1900 H
- Practices: Consult
- Language: ES / EN
- Credits: 60 ECTS
- Registration date: 30-04-2026
- Start date: 24-06-2026
- Available places: 8
387.000 $
Skills and results
What you will learn
1. Development of physical and digital prototypes based on efficient manufacturing criteria.
You will learn to create and validate physical and digital prototypes by applying principles of efficient manufacturing, dimensional accuracy, and resource optimization. You will develop skills in using technologies such as 3D printing, CAD/CAM modeling, and assembly simulations, ensuring that each design iteration is viable, functional, and aligned with industrial production standards.
2. Development of physical and digital prototypes based on efficient manufacturing criteria.
You will learn to manage the entire product lifecycle using PLM/PDM systems to coordinate design, engineering, production, and maintenance. You will develop skills to structure BOMs, control revisions, manage engineering changes, and ensure document traceability, while fostering multidisciplinary collaboration and efficiency in digital industrial environments.
3. Comprehensive user-centered design and validation (from modeling to manufacturing)
You will learn to integrate the entire product development process—from concept to final validation—using user-centered methodologies. You will develop skills in parametric design, ergonomics, simulation, sustainable materials, 3D visualization, and manufacturing management, ensuring efficient, safe solutions that meet current industry standards.
4. Application of user-centered design methodologies and technical ergonomics.
You will learn to apply user-centered design processes by combining research (user profiles, scenarios, journey maps) with technical ergonomics (anthropometry, biomechanics, cognitive load, and ISO standards). You will develop iterative prototypes, conduct usability tests, and analyze eye-tracking data and task times to optimize accessibility, safety, and performance, translating findings into measurable requirements and engineering decisions.
5. Selection and use of sustainable materials and eco-design strategies.
You will learn to identify, evaluate, and apply sustainable materials by considering their life cycle, environmental impact, and technical performance. You will develop skills in eco-design strategies focused on energy efficiency, recyclability, and waste reduction, integrating sustainability criteria into every stage of the design and production process.
6. Surface optimization and high-precision parametric modeling.
You will learn to integrate the entire product development process—from concept to final validation—using user-centered methodologies. You will develop skills in parametric design, ergonomics, simulation, sustainable materials, 3D visualization, and manufacturing management, ensuring efficient, safe solutions that meet current industry standards.
To whom is our:
Interior Design, Packaging & Ergonomics
- Logistics, transportation, and supply chain professionals interested in implementing drones to optimize operations.
- Managers and supervisors at warehouses, distribution centers, and transportation companies looking to improve efficiency and reduce costs.
- Engineers and technicians who wish to acquire specialized knowledge in drone logistics, including route planning, fleet management, and maintenance.
- Entrepreneurs and business owners who wish to start or expand their business in the drone logistics sector by exploring new market opportunities.
- Standards-driven curriculum: You will work with CS-27/CS-29, DO-160, DO-178C/DO-254, ARP4754A/ARP4761, ADS-33E-PRF starting from the first module.
- Accredited laboratories (EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
- Evidence-based Master’s Thesis: safety case, test plan, compliance dossier, and operational limits.
- Industry-led mentorship: faculty with experience in rotorcraft, tiltrotor, eVTOL/UAM, and flight testing.
- Flexible format (hybrid/online), international cohorts, and support from SEIUM Career Services.
- Ethics and safety: a focus on safety-by-design, cyber-OT, DIH, and compliance as pillars.
1.1 Haptic actuators: technologies, performance, and tactile feedback
1.2 Haptic stimulation patterns: sequences, density, and channel combinations
1.3 Usability with gloves: ergonomics, precision, and accessibility of interaction
1.4 Moisture management and environmental conditions: impact on actuator performance
1.5 Design of tangible interfaces: mapping between action, sensation, and feedback
1.6 Modeling and simulation of haptic response: MBSE/PLM for hardware and software
1.7 Calibration and compensation of haptic systems: linearity, drift, and stability
1.8 Safety, compliance, and testing: standards, certifications, and reliability testing
1.9 Integration of haptic sensors: measurement of force, touch, and stiffness
1.10 Case study: usability evaluation with gloves and humidity
2.1 Digital twin and use cases: definition, assumptions, and KPIs
2.2 CAD/CAE data preparation: data cleaning, meshes, and simulation parameters
2.3 Rapid prototyping: 3D printing, light CNC, and validation materials
2.4 Virtual validation: VR/AR for reviews, ergonomics, and walkthroughs
2.5 HIL/SIL integration: test benches, signals, and case orchestration
2.6 DFM/DFA and tolerance stacking: feasibility, cost, and assembly
2.7 Test plan: protocols, acceptance criteria, and traceability
2.8 Data acquisition and analysis: instrumentation, quality, and reproducibility
2.9 Design Correction and Change Management: ECOs, Versions, and Verification
2.10 Case Study: Iteration from Digital Twin to Pilot-Ready Prototype
3.1 Deployment architecture: topologies, environments (dev/stage/prod), and separation criteria
3.2 Advanced CI/CD: pipelines, quality gates, signatures, and immutable images
3.3 Quality assurance: functional and non-functional testing, and HIL/SIL cross-validation
3.4 Cybersecurity in production: hardening, secrets, SBOM, and regulatory compliance
3.5 Observability and SRE: metrics, logs, distributed traces, and error budgets (SLO/SLA)
3.6 Configuration and Change Management: IaC, versioning, feature flags, and safe rollback
3.7 Reliability and Resilience: canary, blue/green, autoscaling, and chaos testing
3.8 Data Management in Deployment: Migrations, Quality, Masking, and Retention
3.9 Operations and Support: Runbooks, Actionable Alerts, MTTR/MTBF, and Incident Response
3.10 Case Study: Canary Deployment with Automated Validation and Controlled Rollback
4.1 Operational Governance: Roles, RACI, and Review Cycles
4.2 Real-Time Observability: Dashboards, Actionable Alerts, and SLO/SLA Reviews
4.3 Continuous Improvement (Kaizen/Lean): Identifying Waste and Value Streams
4.4 Post-Incident Analysis: RCA, Corrective Actions, and Effectiveness Verification
4.5 Cost and Performance Optimization: Rightsizing, Caching, and Resource Tuning
4.6 Vulnerability Management: Patches, Continuous Scanning, and Periodic Audits
4.7 Controlled experimentation: A/B testing, feature flags, and impact telemetry
4.8 Operational quality: automated regression testing and synthetic monitoring
4.9 Knowledge management: runbooks, living documentation, and communities of practice
4.10 Evolutionary roadmap: data-driven prioritization, OKRs, and quarterly reviews
5.1 Governance and Risk Management (GRC): Risk Appetite, Controls, and Criticality Matrix
5.2 Regulatory Compliance: ISO 27001/27701, NIST CSF, GDPR/Privacy, and Audit Evidence
5.3 Zero Trust Architecture and IAM: MFA, RBAC/ABAC, PAM, and Microsegmentation
5.4 Data Protection and Cryptography: Encryption in Transit/at Rest, KMS/PKI/HSM, and Tokenization
5.5 Supply Chain Security: SBOM, Artifact Signatures, SLSA Policies, and Dependencies
5.6 Secure SDLC and DevSecOps: SAST/DAST/IAST, containers, immutable images, and quality gates
5.7 Detection and Response: SIEM/SOAR, EDR, incident playbooks, and continuous improvement
5.8 Resilience and Continuity: BCP/DRP, RTO/RPO, backup/restore testing, and tabletop/chaos exercises
5.9 Vulnerabilities and patches: continuous scanning, CVSS/EPSS prioritization, and remediation SLAs
5.10 Third-party risk and extended continuity: due diligence, contracts, audits, and exit plans
6.1 Fundamentals of applied analytics: metrics, KPIs, and evidence-based decision-making
6.2 Data governance: quality, traceability, and lineage
6.3 Integration of heterogeneous sources: APIs, sensors, and industrial systems
6.4 Descriptive and predictive models: applied statistics and supervised machine learning
6.5 Data visualization and storytelling: dashboards, insights, and executive communication
6.6 Advanced analysis with generative AI: RAG, NLP, and contextual knowledge extraction
6.7 Operational and business indicators: correlation between performance and profitability
6.8 Ethics and compliance in analytics: privacy, biases, and data protection regulations
6.9 Decision automation: smart alerts, triggers, and adaptive systems
6.10 Case study: design of a comprehensive technical and strategic performance dashboard
7.1 Opportunity Discovery: User, Market, and Competitor Research
7.2 Value Proposition and Positioning: Differentiators, JTBD, and Segmentation
7.3 Initiative Prioritization: RICE/WSJF, Dependencies, and Team Capacity
7.4 Living Roadmap: horizons, bets, milestones, and risk management
7.5 OKRs and outcome metrics: strategic alignment and quarterly focus
7.6 Portfolio management: exploration/exploitation balance and resource allocation
7.7 Go-to-Market: launch, pricing, packaging, and commercial enablement
7.8 Stakeholder management: executive communication, agreements, and expectation management
7.9 Impact measurement: NPS/CSAT, adoption, retention, and financial return
7.10 Case study: building an annual roadmap with OKRs and a launch plan
8.1 Open innovation and tech scouting: identifying opportunities and proof of concept
8.2 Intellectual property management: patents, licensing, and freedom to operate (FTO)
8.3 Collaboration with partners: agreements, governance, and win–win models
8.4 Standardization and consortia: interoperability, compliance, and technology readiness level (TRL)
8.5 Applied sustainability: ESG goals, metrics, and actionable reporting
8.6 Circular economy and eco-efficiency: DfR/DfE, recyclability, and footprint reduction
8.7 Responsible supply chain: risk, traceability, and business continuity (BCP)
8.8 Funding and R&D portfolio: CAPEX/OPEX, grants, and prioritization by impact
8.9 Scaling pilots to operations: success criteria, transfer, and adoption
8.10 Case study: sustainable innovation roadmap with KPIs and quarterly milestones
9.1 Change Strategy: Vision, Scope, and Stakeholder Map
9.2 Effective communication: narratives, channels, and expectation management
9.3 Capacity building: training, mentoring, and internal certifications
9.4 Organizational design: roles, RACI, and scaling structures
9.5 Adoption management: user journeys, friction points, and reinforcement plans
9.6 Process standardization: playbooks, SOPs, and version control
9.7 Maturity models: diagnosis, gaps, and evolution plans
9.8 Change metrics: adoption, time-to-value (TtV), and competencies
9.9 Communities of practice: knowledge sharing, repositories, and lessons learned
9.10 Case study: comprehensive change plan with milestones, indicators, and governance
F.1 Project definition: scope, objectives, and alignment with the curriculum
F.2 Analysis of requirements and technical specifications
F.3 Conceptual design and digital modeling: methodologies and tools used
F.4 Development plan: milestones, resources, and timeline
F.5 Technical implementation: module integration, validation, and testing
F.6 Process documentation: traceability, justification, and design decisions
F.7 Evaluation of results: metrics, performance, and achievement of objectives
F.8 Technical presentation and project defense before the evaluation committee
F.9 Professional reflection: lessons learned, innovation, and continuous improvement
F.10 Final delivery: complete portfolio, validated prototype, and roadmap for further development
- Hands-on methodology: test-before-you-trust, design reviews, failure analysis, compliance evidence.
- Software (depending on licenses/partners): MATLAB/Simulink, Python (NumPy/SciPy), OpenVSP, SU2/OpenFOAM, Nastran/Abaqus, AMESim/Modelica, acoustic tools, DO-178C planning toolchains.
- SEIUM Laboratories: scale rotor test bench, vibration/acoustics, EMC/Lightning pre-compliance, HIL/SIL for AFCS, data acquisition with strain gauging.
- Standards and compliance: EN 9100, 17025, ISO 27001, GDPR.
Capstone-type projects
Admissions, fees and scholarships
- Profile: Degree in Computer Engineering, Mathematics, Statistics, or related fields; practical experience in NLP and information retrieval systems is a plus.
- Documents: Updated resume, academic transcript, SOP/statement of purpose, examples of projects or code (optional).
- Process: application → technical evaluation of profile and experience → technical interview → review of case studies → final decision → enrollment.
- Fees:
- Lump-sum payment: 10% discount.
- Payment in 3 installments: no fees; 30% upon enrollment + 2 equal monthly payments of the remaining 35%.
- Monthly payment: available with a 7% fee on the total; annual review.
- Scholarships: based on academic merit, financial need, and promoting inclusion; agreements with companies in the sector for partial or full scholarships.
See “Calendar & Calls for Applications”, “Scholarships & Financial Aid”, and “Tuition & Financing” in the SEIUM mega-menu
Do you have any questions?
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F. A. Q
Frequently Asked Questions
Yes, we have international certification.
Yes: experimental models, real-world data, applied simulations, professional environments, real-world case studies.
It is not required. We offer leveling tracks and mentoring
Absolutely. It covers electric propulsion, integration, and emerging regulations (SC-VTOL).
Recommended. There are also internal challenges and consortia.
Yes. Online/hybrid format with scheduled labs and visa support (see “Visa & Residence”).