Design reconfiguration in modern manufacturing represents a paradigmatic shift toward adaptive, flexible production systems that can rapidly respond to changing market demands and product requirements. The Asset Administration Shell (AAS) is the standardized digital representation of an asset, the corner stone for the interoperability of Industrie 4.0 components organized in Industrie 4.0 systems, forming the Industry 4.0 Component with the physical asset.
Within the MODAPTO framework, design reconfiguration encompasses the systematic approach to creating, managing, and optimizing modular manufacturing systems through standardized digital representations and process models.
The concept builds upon the foundation of Reconfigurable Manufacturing Systems (RMS), which uniquely explores the state-of-the-art in distributed and decentralized machine control and machine intelligence, incorporating RMS fundamentals, design rational, economic benefits, needs and challenges, as well as advanced distributed control systems.
MODAPTO’s approach to design reconfiguration integrates three core components: physical production modules with specific manufacturing capabilities, their corresponding digital twins for monitoring and control, and standardized interfaces that enable seamless integration and reconfiguration.
The implementation of Reconfigurable Manufacturing Systems (RMS) offers decision-makers an efficient solution to cope with changes caused by highly fluctuating demand and customer requirements, though these systems require a large number of modifications handled by workforces who must have adequate qualification and skills.
The MODAPTO design reconfiguration methodology addresses this challenge by providing structured frameworks for both technical implementation and workforce development.
Contemporary manufacturing environments demand unprecedented levels of flexibility and responsiveness. Traditional fixed automation systems, while efficient for high-volume production, lack the adaptability required for today’s diverse product portfolios and shorter product lifecycles. Design reconfiguration through MODAPTO enables manufacturers to create production systems that can be rapidly reconfigured at multiple levels – from individual machine parameters to entire production line layouts – without requiring complete system redesign or replacement.
The integration of standardized frameworks such as the Asset Administration Shell (AAS) for digital asset representation and Business Process Model and Notation (BPMN) for process definition creates a comprehensive ecosystem for design reconfiguration. The AAS is one of the most underestimated core elements of digitalization, enabling seamless interoperability and continuous communication of all devices from shop floor to management, from supplier to customer and across all product life cycles.
This standardization ensures that reconfiguration decisions can be made based on accurate, real-time information about system capabilities, performance, and constraints.
The purpose of this learning module is to equip manufacturing professionals, system designers, and digital transformation specialists with comprehensive knowledge and practical skills in design reconfiguration methodologies within the MODAPTO framework. This module addresses the critical need for adaptive manufacturing systems that can respond to market volatility, product customization demands, and operational efficiency requirements while maintaining high quality standards and minimizing reconfiguration costs.
The target audience for this learning module encompasses a diverse range of manufacturing professionals who are involved in system design, implementation, and management within Industry 4.0 contexts. Primary participants include manufacturing engineers who are responsible for production system design and optimization, automation engineers working with programmable logic controllers and industrial control systems, and digital transformation specialists leading Industry 4.0 initiatives within their organizations.
System integrators and technical consultants who work across multiple manufacturing organizations represent another key audience segment. These professionals require deep understanding of standardized approaches to ensure interoperability between different vendors’ systems and to provide consistent, reliable solutions across diverse industrial environments. Many vertical industries and various teams use digital twins – design and construction engineers use them for collaborative development, process engineers for exploring improvements, operations teams for training, and asset reliability teams for predictive maintenance.
Production managers and operations supervisors who oversee day-to-day manufacturing activities need this knowledge to make informed decisions about system modifications, capacity adjustments, and process improvements. The workforce qualification framework in RMS ensures skills needed for performing activities, with modular approaches for workforce skills management and building training modules linked to qualification phases.
Understanding design reconfiguration principles enables these managers to optimize resource utilization and respond effectively to changing production requirements.
Research and development professionals working in advanced manufacturing technologies form another important audience segment. These individuals need comprehensive understanding of emerging standards, integration methodologies, and practical implementation challenges to develop next-generation manufacturing solutions. Academic researchers and university faculty members teaching advanced manufacturing courses also benefit from this module’s structured approach to complex technical concepts.
Plant engineers and maintenance professionals represent a critical audience segment, as they are responsible for ensuring system reliability and performance throughout reconfiguration processes. Digital twins provide numerous advantages in manufacturing including process optimization, monitoring, streamlined processes, safer and faster repairs, more efficient training, and accelerated pace of work.
These professionals need to understand how reconfiguration affects maintenance requirements, spare parts management, and system diagnostics.
Quality assurance professionals and compliance managers also benefit significantly from this module, as they must ensure that reconfigured systems maintain quality standards and regulatory compliance. Understanding how standardized digital representations and process models support traceability, validation, and documentation requirements is essential for these roles.
Upon successful completion of this learning module, participants will demonstrate comprehensive competency in design reconfiguration methodologies within the MODAPTO framework. The learning outcomes are structured to progress from foundational understanding through practical application to advanced optimization and strategic implementation capabilities.
Participants will be able to analyze existing manufacturing systems and identify opportunities for modular reconfiguration, evaluating technical feasibility, economic benefits, and implementation challenges. Companies must increase their flexibility and enable high product customization to meet market demands, requiring modular, reconfigurable assembly systems that allow unrestricted connection of individual modules and fulfill changeability requirements at different production levels.
This analytical capability includes understanding the hierarchical nature of MODAPTO modules at stage, cell, and individual equipment levels.
A fundamental learning outcome involves mastering the creation and management of Asset Administration Shell (AAS) models for manufacturing assets. Participants will demonstrate proficiency in defining AAS structures, implementing standardized submodels, and ensuring compliance with international standards. The AAS includes submodels characterizing assets by describing aspects in different domains including identification, communication, engineering, safety, security, lifecycle status, energy efficiency, and health status, with each submodel described by properties defined by unique global identifiers.
This includes practical skills in AAS serialization, validation, and integration with existing enterprise systems.
Participants will develop advanced competency in Business Process Model and Notation (BPMN) for manufacturing process definition and optimization. Business Process Model and Notation is the global standard for process modeling, with visual nature enabling greater collaboration between different teams and helping align different groups to better understand and represent process design.
This encompasses creating production schemas, modeling complex workflows with parallel processing and conditional logic, and mapping BPMN models to executable manufacturing processes.
Integration and interoperability skills represent critical learning outcomes, with participants demonstrating ability to export design configurations to MODAPTO Digital Twin Manager and MessageBus systems. Digital twin technology like AWS IoT TwinMaker helps optimize operations and performance by creating digital twins of real-world systems, providing tools to digitally replicate buildings, factories, manufacturing facilities, production lines, and industrial equipment.
This includes understanding communication protocols, data exchange formats, and system validation procedures.
Strategic implementation capabilities form advanced learning outcomes, enabling participants to lead design reconfiguration projects within their organizations. This includes change management skills, stakeholder engagement strategies, and performance measurement frameworks for reconfiguration initiatives. The approach provides a structured yet flexible framework for implementing digital twins, leveraging capabilities to enhance each process step and creating tailored solutions that align with facility-specific needs and goals.
Participants will also develop troubleshooting and optimization skills, enabling them to diagnose reconfiguration issues, implement performance improvements, and maintain system efficiency throughout the asset lifecycle. This includes understanding predictive maintenance approaches, performance monitoring strategies, and continuous improvement methodologies within reconfigurable manufacturing environments.
Participation in this Design Reconfiguration learning module requires foundational knowledge and experience in manufacturing systems, automation technologies, and digital systems integration. Participants should possess undergraduate-level understanding of manufacturing processes, industrial automation principles, and basic programming concepts. Prior exposure to programmable logic controllers (PLCs), human-machine interfaces (HMIs), and manufacturing execution systems (MES) is highly recommended to maximize learning effectiveness.
Experience with networked industrial systems, Ethernet-based communication protocols, and cybersecurity fundamentals provides essential background for understanding integration challenges and solutions.
Professional experience requirements include a minimum of two years in manufacturing, automation, or related technical fields. Participants should have direct involvement in production system operations, maintenance, or improvement projects. Experience with smart sensors, industrial communication systems, and understanding of manufacturing processes such as inventory control, inspection, sorting, assembly, torqueing, testing, and storage provides valuable context for advanced concepts.
Management-level participants should have responsibility for production system decisions or strategic planning initiatives.
Educational background should include engineering degree (mechanical, electrical, industrial, or related field) or equivalent technical education combined with substantial practical experience. Modular courses designed as 5-week curricula review critical topics in advanced manufacturing environment and utilize real-world equipment for project-based learning at fundamental, intermediate, and advanced levels.
Participants without formal engineering education should demonstrate comparable technical competency through professional certifications or extensive hands-on experience.
Software prerequisites include proficiency with Microsoft Windows operating systems, basic understanding of XML and JSON data formats, and comfort with web-based applications. Adopting modeling software based on BPMN and DMN standards allows managing and optimizing manufacturing processes in smart and efficient ways, as demonstrated by successful implementation in various manufacturing contexts.
Participants should be prepared to work with specialized modeling tools and cloud-based platforms during practical exercises.
Language requirements specify intermediate English proficiency for technical communication, as course materials, standards documents, and software interfaces are primarily in English. Participants should be comfortable reading technical documentation, participating in group discussions, and completing written assessments in English.
