Registration Open

Breakfast Networking Session

Chairman’s Welcome Session

OEM CASE STUDY

Transitioning GM To A Smart Manufacturing Environment

Aaron K. Dunlap, ME Tech Fellow, Manufacturing Execution Systems-Architect ME Vehicle Systems – General Motors

Technical Challenges in Smart Manufacturing

• Address diverse data sources and misalignment in data definitions

• How to develop strategies for managing and storing the increasing volume of data

• Balancing  enhanced cybersecurity measures with uninterrupted manufacturing

• How to overcome communication disruptions due to cybersecurity protocols

• Ensuring  focused and beneficial AI implementations

• Leverage AI in robotics and vision systems for improved efficiency

• Debating the scope of digital twins: entire plant vs. critical areas

• Assess time and financial investments for digital twin development

Opportunities for Vendor Collaboration

• Identifying vendor solutions to address GM’s specific challenges

• Developing tailored strategies to enhance smart manufacturing capabilities

Aligning Strategies with Industry Trends

• Examining GM’s current uses of AI, MES, and other technologies

• Learn from industry best practices and avoid common pitfalls

• Align GM’s strategic plans with emerging technologies and evolving demands

OEM PANEL

SMART Manufacturing In The Digital Age

Miguel Saez Ph.D., Manager, Automation Execution – General Motors 

Brian Breuhan, Global Manufacturing Optimization Strategist – General Motors 

Aaron K. Dunlap, ME Tech Fellow, Manufacturing Execution Systems-Architect ME Vehicle Systems – General Motors

Michael Flynn, Data Science, Analytics, & Product Management –  Rivian

Madhu Rao, Senior Engineer – Chassis Engineering, Product Development,  IoT – Tesla

David Dobbs, Director of Operations, PTO – Harley Davidson

Matt Myrand, Manufacturing Innovation Director – FORVIA

Fernando Bera, Engineering Supervisor –  ZF Group

Ashish Saxena, President  –   Innova Solutons

Konstantin Popov, VP, Enterprise Technology & Financial Management –  Cprime

Discussion Points for Panel:

• How the Internet of Things (IoT) and Artificial Intelligence (AI) are revolutionizing automotive manufacturing, enabling predictive maintenance, real-time monitoring, and adaptive production processes

• The role of digital twins and simulation in optimizing production workflows, reducing time to market, and enhancing product quality through virtual prototyping and testing

• Examining the impact of robotics and automation on assembly lines, highlighting advancements in collaborative robots (cobots), autonomous mobile robots (AMRs), and automated guided vehicles (AGVs) for increased flexibility and agility

• Learn how data analytics and visualization tools are being utilized to analyse vast amounts of manufacturing data, uncover insights, and optimize decision-making processes for continuous improvement

• The cybersecurity challenges inherent in smart automotive manufacturing, including protecting sensitive data, securing interconnected systems, and mitigating potential cyber threats to ensure operational resilience

• Strategies for optimizing supply chain management in the automotive industry, leveraging smart technologies such as blockchain for transparent and efficient logistics, inventory management, and supplier collaboration

• Highlight the importance of workforce upskilling and training programs to empower employees with the necessary skills to thrive in an increasingly digitalized manufacturing environment, fostering innovation and competitiveness

DIGITAL TWINS

Digital Twins And The Industrial Metaverse In Data Driven Manufacturing

Brian Breuhan, Global Optimization Strategist – General Motors 

• Understand types of digital twins across the product lifecycle and how they are used in the concept, create, operate, and dispose phases, aiding in virtual modelling, testing, real-time monitoring, and sustainable disposal

• Reveal how digital twin can offer benefit without physical counterparts and enable early design validation, cost-efficient virtual testing, accelerated development, and risk mitigation, eliminating the need for initial physical prototypes

•  Discuss the value in the create phase and how digital twins maximise value by moving physical testing and validation to the virtual realm, optimising designs, and saving resources during the product development phase

• Investigate the possibilities of time manipulation in simulations that allows forward and backward time simulations, predictive maintenance, and scenario analysis, providing insights into future performance and potential degradation

• Explore industrial metaverse integration and how it connects digital twins with IIoT and extended reality, enhancing real-time collaboration, decision-making, and seamless transitions between the physical and digital worlds

WORKFORCE

Innovations In Predictive Maintenance, Supply Chain Resiliency, Blockchain, Digital Twins, Sustainability, And Workforce Development

Ragu Athinarayanan, Director, Smart Manufacturing Innovation Center Purdue University

Revolutionizing Maintenance With Predictive Technologies

• Discover how Industry 4.0 and IoT sensors enable predictive maintenance, minimizing downtime and reducing costs

• Advanced analytics and machine learning predict equipment failures, optimizing maintenance schedules and extending equipment lifespan

Enhancing Supply Chain Resiliency And Risk Management

• Explore how IoT and real-time monitoring improve supply chain visibility, allowing quick responses to disruptions

• Advanced analytics and AI models facilitate robust contingency planning, ensuring continuous production during unforeseen events

Boosting Supply Chain Visibility With Blockchain Technology

• Learn how blockchain ensures transparency and traceability, improving accountability from origin to end customer

• Blockchain enhances efficiency in supply chain processes, such as inventory management and compliance verification

Harnessing Digital Twins For Manufacturing Excellence

• Digital twins create virtual replicas using real-time IoT data, optimizing production processes and reducing risks

• They diagnose issues and predict maintenance needs, improving decision-making and product quality

Promoting Sustainability In Manufacturing

• Advanced Industry 4.0 technologies enhance resource efficiency, reducing waste and minimizing environmental impact

• Smart factories optimize energy consumption and adopt circular economy practices, promoting eco-friendly manufacturing

DATA & ANALYTICS

Shifting Gears: How Automation Fueled By Industrial DevOps Is Reshaping Automotive Manufacturing

Ben O’Rourke, Chief Revenue Officer, Copia Automation

• Highlight the transformative shift in the automotive industry where the sector is rapidly evolving with increased automation and digitalization, driven by the need to optimise production lines, improve efficiency, and enhance product quality. This transformation is essential for maintaining competitiveness in a fast-changing market

• Insights from Industry Leaders: The State of Industrial DevOps Report, based on insights from 200 senior-level manufacturing executives across North America, highlights how leading automotive manufacturers are successfully implementing automation technologies. These insights provide valuable benchmarks and strategies for other companies looking to follow suit

• Reveal how industrial DevOps are critical in accelerating the adoption of automation. By integrating development and operations processes, it helps maximise the impact of automation technologies, ensuring smoother implementation, faster iteration, and continuous improvement in manufacturing operations

• Emphasise that leveraging Industrial DevOps not only facilitates the adoption of advanced automation but also offers a significant competitive advantage. Companies that effectively implement these practices can achieve higher efficiency, better product quality, and overall enhanced operational performance, positioning themselves ahead in the industry

QUALITY

How Predictive Quality Leverages Machine Learning And Manufacturing Data To Detect Defects In Real Time And Perform Faster Root Cause Analysis

Aaron Alberts, Vice President – Customer Success, Acerta

• Understand how Industry 4.0’s advancements in industrial data collection, machine learning, and cloud computing have enabled the development of predictive quality solutions that integrate seamlessly into manufacturing processes

• Learn how predictive quality software ingests and analyzes data from various sources, such as process parameters, product attributes, and test data, to identify hidden links and improve quality insights

• The importance of real-time data ingestion and automated root cause analysis that allow manufacturers to quickly identify and address quality issues, reducing downtime and enhancing efficiency

• How to maintain product quality with machine learning algorithms that detect anomalies in manufacturing data, providing alerts for potential defects and enabling timely interventions

• Discuss how predictive analytics provides immediate, real-time and actionable insights that can greatly improve the ability to perform root cause analysis and even guide business decisions

Morning Networking Break

Sponsor

AI & GEN AI

AI For Automated Generation Of Robot Programs For Complex Manufacturing Tasks: From Ideation To Implementation

Miguel Saez Ph.D., Manager, Automation Execution – General Motors 

• Understand how developing robot paths for various manufacturing applications remains a time-consuming and resource-intensive task. The manual programming of these paths requires significant expertise and is essential for ensuring safe and collision-free robot movements, which impacts overall efficiency and productivity

• Highlight the use of Reinforcement Learning (RL) to automate the generation of optimal robot paths in manufacturing environments. By leveraging AI algorithms and simulation or off-line programming tools, RL can create paths that are shorter and faster, minimising cycle times and maximising robot utilisation

• Reveal how AI-generated paths can significantly reduce cycle times, leading to enhanced robot utilisation and overall operational efficiency. The optimization of robot movements and the reduction in programming time result in higher throughput and increased production output

• Discuss AI’s ability to adapt to changes in the environment or production tasks without manual intervention allows for the automatic generation of new optimal paths. This flexibility ensures that manufacturing operations remain efficient and responsive to varying conditions and requirements

• Explain how AI can continuously learn and improve path generation based on real-time data, leading to ongoing efficiency gains. The implementation of AI-driven robot path generation in real robotic assembly cells demonstrated significant potential to revolutionise manufacturing operations, contributing to a more competitive and sustainable manufacturing landscape

Bridging The Gap: Why Can’t My ERP Talk To My MES?

Mike Bastian, Advanced and Digital Manufacturing Engineering Manager – Ford

• Exploring the technical challenges and common barriers to integration between Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES)

• The impact of these integration challenges on operational efficiency and data consistency

• Discussing best practices and technological solutions for achieving seamless integration between ERP and MES systems

• Differences in data models and structures.

• Communication protocols and interface standards

• Legacy systems and compatibility issues

• Data inconsistency and redundancy

• Disconnected workflows and lack of real-time visibility

• Inefficiencies in production planning and execution

• Best Practices for ERP-MES Integration

• Data Mapping and Standardization

• Middleware and Integration Platforms

• API and Web Services

• Advantages of using cloud-based solutions for ERP-MES integration

• Enhancing integration with Industrial Internet of Things (IIoT) devices

NETWORK

The Potential Power Of Edge Computing For Real-Time Data Processing In Automotive Smart Manufacturing

Rajeev Puri, Vice President, Distinguished Engineer, and CTO US Manufacturing, Kyndryl

• Reducing Latency: Edge computing brings data processing closer to the source, minimizing latency and enabling near-instantaneous decision-making in automotive manufacturing environments. This ensures timely responses to critical events and enhances overall operational agility

• Enabling Real-time Insights: With edge computing, automotive manufacturers can analyze data in real-time, gaining actionable insights into production processes, equipment performance, and quality control. This enables proactive maintenance, optimized resource allocation, and improved product quality

• Enhancing Scalability: Edge computing enhances the scalability of data-intensive applications in smart manufacturing by distributing computational tasks across edge devices. This allows automotive manufacturers to efficiently manage large volumes of data generated by IoT devices, sensors, and production systems

• Empowering Predictive Maintenance: By deploying edge computing solutions, automotive manufacturers can implement predictive maintenance strategies that anticipate equipment failures before they occur. This minimizes unplanned downtime, extends asset lifespan, and reduces maintenance costs

• Driving Innovation: Edge computing unlocks new opportunities for innovation in automotive smart manufacturing, enabling the development of advanced AI algorithms, autonomous systems, and predictive analytics tools. By leveraging edge computing capabilities, manufacturers can stay at the forefront of technological advancements and maintain a competitive edge in the industry

AI & GEN AI

Leveraging AI And Analytical Efficiency For Predictive Maintenance

Dr. Jeremy Frank, co-founder and CEO, KCF Technologies

• The Evolution of Data Analysis: A brief overview of how data analytics has evolved over the years, shifting from manual spreadsheets to automated algorithms, and the current challenges that demand more sophisticated approaches

• Machine Learning and AI: An introduction to some of the groundbreaking computational methods reshaping the way we view and analyze data. This includes machine learning and other forms of artificial intelligence that can process and interpret data at unprecedented scales and speeds

• Practical Applications and Case Studies: Demonstrations of real-world scenarios where these techniques have been applied, highlighting their successes, and importantly, the lessons learned from their failures

• Advantages of New Technology: A discussion on the merits of integrating these advanced techniques, their potential to reduce human error, increase speed and efficiency. Most importantly, with the challenging work force, how to elevate people using technology

• Best Practices for Implementation: Concrete steps and recommendations for organizations looking to harness these techniques

Networking Lunch Break

Soup, Salad, Mains, Sides, Dessert

Tea, Coffee, Juices, Soft Drinks

DATA & ANALYTICS

How Automakers Can Deploy Analytics At Scale Using A Hybrid Cloud Strategy

Vikram Mankar, Principal Product Manager – GE Vernova

In the realm of automotive manufacturing, the effective use of operational data is crucial for innovation and efficiency. However, it is a well-known fact that most companies utilize less than 1% of their operational data. This session will explore how automotive manufacturers can leverage Smart Factory innovations to maximize the potential of their data. By deploying a hybrid cloud strategy, automakers can empower their workforce, democratize data, and implement advanced monitoring and analytics applications. Attendees will gain insights into practical methods for overcoming current and future manufacturing challenges through scalable analytics solutions.

• Learn how automakers can enable their domain experts to harness the power of analytics and machine learning (ML) tools. By providing plant floor professionals with the right analytical tools, manufacturers can solve complex production challenges more effectively and improve operational efficiency

• Understand the importance of making data accessible to everyone within the organization. Democratizing data involves breaking down silos and ensuring that data is available to all relevant stakeholders, enabling them to make informed decisions based on comprehensive insights

• Discover how hybrid cloud architecture facilitates condition-based monitoring and other critical applications. Hybrid clouds combine on-premises infrastructure with cloud services, offering flexibility, scalability, and enhanced data security, essential for modern automotive manufacturing environments

• Explore strategies for scaling analytics across the entire organization. This involves implementing robust data management frameworks, adopting scalable cloud solutions, and ensuring that analytics tools are integrated seamlessly into existing workflows to drive continuous improvement and innovation

• Gain insights into how Smart Factory innovations can help automotive manufacturers not only tackle current production challenges but also anticipate and mitigate future issues. By leveraging advanced analytics and a hybrid cloud strategy, companies can stay ahead of the curve and maintain a competitive edge in the evolving automotive industry

DATA & ANALYTICS

Revolutionizing Automotive Manufacturing: How Ford Is Leveraging Generative AI, ML Anomaly Detection, Computer Vision, And Connected Vehicle Streaming Data To Transform The Industry

Rajeev Kalamdani, Director, Manufacturing & IIoT Analytics – FORD

• The automotive manufacturing industry stands on the brink of a revolution, fueled by cutting-edge technologies like Generative AI, ML Anomaly Detection, Computer Vision, and Connected Vehicle Streaming Data. Let’s break down how each of these technologies is making its mark using real life examples from Ford:

• Generative AI (using LLMs): Still in early stages, but showing promise for automating design processes, generating code for manufacturing systems, and creating technical documentation. Challenges include ensuring accuracy, addressing potential bias, and explaining AI-generated outputs

• ML Anomaly Detection: A mature technology already used for predictive maintenance (reducing downtime), real-time quality control (catching defects early), and process optimization (identifying bottlenecks). The need for large training datasets and adaptation to new processes are ongoing challenges

• Computer Vision: Widely used for robot guidance, worker safety monitoring, and automated quality inspection. Challenges include developing robust algorithms that handle varying lighting and environmental conditions

• Connected Vehicle Streaming Data: Early adoption, but holds massive potential for improving vehicle performance, enhancing predictive maintenance with real-time data, and even enabling personalized manufacturing in the future. Data privacy and security are paramount concerns that need to be addressed

The automotive manufacturing landscape is being reshaped by these powerful technologies. While challenges remain, the potential benefits in terms of efficiency, quality, safety, and personalization are enormous. We are only beginning to scratch the surface of what’s possible with AI, ML, and connected data in this exciting field.

FINANCE

Faster To Showroom, Faster To Profits: Align Cutting-Edge Enterprise Operating Models, Platforms, And Technology

Konstantin Popov, VP, Enterprise Technology & Financial Management, Cprime

This session will explore how modern enterprise operating models, unified technology solutions, and integrated platforms can help automotive companies drive progress, streamline operations, accelerate innovation, and ultimately improve financial performance. Align your way of working with the right tooling to empower your organization to:

• Alignment: Align enterprise strategy with team-level execution, ensuring optimal resource allocation and faster time-to-market, leading to increased revenue and market share

• Optimization: Leverage strategic portfolio management to optimize labor and resource deployment, expediting the delivery of innovative features and technologies while controlling costs and maximizing return on investment

• Efficiency: Utilize predictive maintenance, digital twin simulations, and advanced analytics to streamline vehicle development and reduce manufacturing downtime, minimizing the financial impact of production delays

• Adaptability and Innovation: Harness real-time data and AI to optimize the supply chain, minimize bottlenecks, and rapidly adapt to evolving consumer demands, preventing lost revenue due to missed market opportunities

• Collaboration: Effectively manage workforce and vendor dependencies to ensure seamless collaboration and timely delivery of projects, avoiding costly delays and budget overruns

• Actionable insights and practical strategies to reduce time to market for new vehicles, improve production efficiency, control program costs, increase overall equipment effectiveness (OEE), and drive profitability

• Best practices for aligning strategy, execution, and technology to drive automotive progress, prevent costly delays, and optimize financial performance

• Real-world examples of how automotive companies have successfully navigated the rapidly evolving landscape, secured their position at the forefront of the industry, and improved their bottom line

SOFTWARE

Accelerating Vehicle Design And Engineering With Advanced ALM/PLM Systems And Comprehensive Software Solutions

Ali Faraj, Chief Technology Officer, Cognizant

This session will delve into the advanced Application/Product Lifecycle Management (ALM/PLM) systems in the design and engineering of new vehicles. Attendees will gain insights into how collaboration with OEM engineering groups and Tier 1 suppliers enhances the conceptualization, design, development, and validation of vehicle components and systems.

• How ALM/PLM systems improve development and validation processes

• Product Architecture: Designing robust and scalable vehicle components

• DevOps Processes: Streamlining development with continuous integration and delivery

• Rapid Prototyping and UX: Accelerating innovation with rapid prototyping and user experience design

• Software Development: Best practices for developing high-quality automotive software

• Product Testing and Integration: Ensuring reliability and performance through rigorous testing and seamless integration

• Infrastructure Management: Managing the underlying infrastructure for optimal performance

• Tools and frameworks that expedite development cycles

• Live demonstration of an integrated ALM/PLM system in action

AI & GEN AI

The Future Is Now: AI In Automotive Manufacturing

Patrick Tew, Enterprise Sales Manager, MakinaRocks

• Discover how AI’s rapid evolution is revolutionizing automotive manufacturing, enhancing anomaly detection, predictive maintenance, and overall production quality

• Understand why conventional AI initiatives often fail due to barriers like insufficient data and conservative practices, and learn strategies to overcome these challenges

• Explore the success of AI projects that are specifically tailored to the complexities of automotive manufacturing

• Learn about the specific benefits of AI for manufacturing, including higher-quality parts, cost savings, minimized downtime, and improved efficiency

• Take action now to leverage AI in your automotive manufacturing processes, gaining a competitive edge with faster, more efficient operations and lower costs

DATA & ANALYTICS

Bridging The Gap By Achieving Interoperability In Automotive Manufacturing

Michael Flynn, Data Science, Analytics, & Product Management – RIVIAN

• Highlighting the critical role of interoperability in facilitating seamless data exchange and collaboration among diverse systems, applications, and devices within the automotive manufacturing ecosystem

• Discussing the challenges faced in achieving interoperability, such as disparate data formats and protocols, and presenting strategies and solutions for overcoming these challenges through standardization and integration efforts

• Exploring existing standardization initiatives and frameworks aimed at promoting interoperability in automotive manufacturing, including efforts to standardize data formats, communication protocols, and interfaces across different systems and devices

• Illustrating the benefits of interoperability, such as improved efficiency, enhanced productivity, reduced operational costs, and increased flexibility in adapting to changing market demands and technological advancements

• Sharing best practices and real-world case studies of successful interoperability implementations in automotive manufacturing, highlighting lessons learned, key success factors, and recommendations for industry stakeholders embarking on interoperability initiatives

DATA & ANALYTICS

How Digital Manufacturing Optimizes Production Through Process Transparency

Rick Homman, Dir. Manufacturing,  FORCAM US

• Understanding that basic Lean Principles Haven’t Changed and are still the best way to run your plant

• Explaining why digital Transformation is not about replacing those basics, it is about allowing them to work better than they ever have before

• Presenting a case study on the voice of the machine

• Discuss three things you can do today if you are not already – pick one bottleneck and work through the theory of constraints, measure OEE and democratize downtime resolutions

• The advantages of using data pushes and the ability to resolve downtime problems farther down the org chart

• Define why things are working, and why they are not – why does something work? Can it be repeatable?

• Identifying the primary reasons that something is not working? How do we control that?

Afternoon Networking Break

Tea, Coffee, Soft Drinks, Donuts, Snacks

Sponsor

ROBOTS & AUTOMATION

Unlocking Efficiency: Why Every Vehicle Factory Needs Automated Vehicle Marshalling (AVM)

George Geros, Commercial Director, Embotech AG

• Explore the technological underpinnings of AVM. Gain insights into the advanced systems, including sensors, machine learning algorithms, and real-time data processing, that enable AVM to optimize vehicle movements

• Understand how these technologies integrate to streamline operations and enhance efficiency

• Discover how AVM effectively addresses the limitations and inefficiencies of traditional vehicle marshalling methods and tackle traditional bottlenecks

• Learn about specific challenges such as congestion, scheduling conflicts, and human error, and see how AVM provides innovative solutions to enhance productivity and reduce downtime in factory environments

• Look into the future possibilities and broader applications of AVM technology and discuss potential uses in diverse industries

• Understand the scalability and adaptability of AVM for various logistical challenges

DIGITAL TWINS

Unveiling The Power Of Digital Twins For Automotive Manufacturing Process Optimization

Michael Bradford, DELMIA Strategic Business Development Director, Dassault Systemes

• Explore how digital twins simulate production workflows, providing insights into potential bottlenecks and inefficiencies in automotive manufacturing processes

• Discover the benefits of real-time monitoring enabled by digital twins, allowing manufacturers to track production metrics and make informed decisions to optimize operations instantly

• Learn how digital twins help automotive companies optimize resource utilization by identifying areas of over or underutilization, leading to cost savings and improved productivity

• Understand how digital twins facilitate waste reduction strategies by pinpointing areas of waste generation and enabling targeted interventions to minimize waste generation and disposal

• Explore how the integration of digital twins fosters a culture of continuous improvement in automotive manufacturing, driving ongoing optimization efforts to maximize efficiency and competitiveness

NETWORKING

Vastly Reduce Your Ethernet Network Downtime By Solving Most Factory Floor Networking Problems In Five Minutes Or Less

John S. Rinaldi, CEO and Business Development Manager, Real Time Automation

• Understand the inevitability of Ethernet network failures due to various factors such as physical wear and tear, bandwidth overload, and human error

• Learn how to identify the common causes of network failure and the impact they can have on factory operations

• Gain knowledge on proactive measures to minimize the risk and frequency of these failures

• Recognize the significant financial impact of network downtime, with costs ranging from hundreds to tens of thousands of dollars per minute

• Understand how to calculate the true cost of downtime in your specific environment and the importance of minimizing these interruptions to maintain productivity and profitability

• Learn strategies for reducing downtime and its associated costs

• Evaluate the limitations of current tools and technologies used for Ethernet network management on the factory floor

• Understand why traditional methods fall short in predicting, diagnosing, and resolving network issues promptly

• Learn about the gaps in existing solutions and the need for more advanced, real-time tools that can provide accurate diagnostics and faster resolutions

CYBERSECURITY

Securing Connected Ecosystems: Cybersecurity Strategies For Modern Automotive Factories

• Understanding the Risks: Gain insight into the cybersecurity risks posed by connected ecosystems in automotive manufacturing, including the expanded attack surface, potential vulnerabilities in IoT devices, and the implications of insider threats

• Securing IoT Devices: Learn best practices for securing IoT devices in automotive factories, including device authentication, encryption protocols, and continuous monitoring to detect and respond to anomalous behaviour

• Implementing Network Segmentation: Explore the importance of network segmentation in isolating critical production systems from non-essential networks, reducing the impact of cyberattacks and limiting lateral movement within factory environments

• Leveraging Threat Intelligence: Discover how automotive manufacturers can leverage threat intelligence to proactively identify and mitigate emerging cyber threats, enhancing their ability to anticipate and respond to cyber incidents effectively

• Building a Culture of Cybersecurity: Understand the importance of fostering a culture of cybersecurity awareness and accountability among employees in automotive manufacturing facilities, empowering them to recognize and report suspicious activities and adhere to security policies and procedures

AI & GEN AI

Leveraging Smart Factory Strategies For Enhanced Problem-Solving

Fernando Bera, Engineering Supervisor – ZF Group

This session aims to provide insights into the effective integration of process expertise and Smart Factory strategies to address and resolve complex manufacturing issues and share the experiences gained in ZF’s implementation of a Broach Quality System.

• Understand the synergy between process experts and Smart Factory technologies in problem-solving

• Learn how leveraging the deep knowledge of process experts alongside advanced Smart Factory strategies can lead to innovative solutions and improved operational efficiency

• Explore case studies and real-world examples where this combination has successfully addressed complex manufacturing challenges

• Gain insights into the strategic decision-making process for implementing Smart Factory/Industry 4.0 solutions

• Learn about the advantages and disadvantages of building custom solutions in-house versus purchasing ready-made solutions from external vendors

• Understand the factors to consider, such as cost, scalability, integration capabilities, and long-term maintenance, to determine the best approach for your organization

• Explore the challenges associated with connecting and integrating data from various industrial devices in a Smart Factory environment

• Learn about alternative methods and emerging technologies that simplify connectivity and data integration

• Understand how to overcome common connectivity issues to ensure seamless data flow and real-time monitoring across your manufacturing operations

• Identify and understand the common traps and pitfalls associated with implementing Industry 4.0 initiatives

• Learn about potential challenges such as technology integration issues, data security concerns, workforce adaptation, and unrealistic expectations

• Gain practical knowledge on how to navigate these traps, mitigate risks, and ensure a successful and sustainable Industry 4.0 transformation

DATA & ANALYTICS

A Strategic Approach To Achieving Success At Scale From A Proof Of Concept

Ed Lesnau, Director, Industry Digital Strategy Automotive Americas, Microsoft

• Understand the foundational role a robust and secure data estate plays in digital transformation. Learn how to develop a comprehensive data strategy that ensures data integrity, security, and availability. Explore methods to integrate data from diverse sources, enabling seamless access and analysis, while ensuring compliance with data protection regulations

• Gain insights into designing and implementing a hybrid-cloud architecture that combines the benefits of both on-premises and cloud environments. Learn how hybrid-cloud solutions can provide the flexibility and scalability needed to support evolving business requirements. Discover key enabling technologies and practices for optimizing performance, cost-efficiency, and security in a hybrid-cloud setup

• Explore strategies for identifying and prioritizing use cases based on their potential business value and the time required to realize that value. Learn to evaluate use cases through a balanced lens, considering factors such as ROI, strategic alignment, feasibility, and resource availability. Understand how to create a roadmap that aligns short-term wins with long-term objectives to ensure sustained progress and stakeholder buy-in

• Learn how to design programs and projects with scalability in mind from the outset. Understand the importance of developing standardized processes, templates, and tools that can be reused across multiple initiatives. Explore best practices for creating and managing a repository of repeatable assets, ensuring consistency and efficiency in program roll-out. Discover techniques for measuring and optimizing scalability efforts to maintain momentum and achieve wide-reaching impact

ROBOTS & AUTOMATION

Empowering Human-Robot Collaboration By Unleashing The Potential Of Collaborative Robots

• Exploring Collaborative Robotics: Delve into the world of collaborative robots (Cobots) and their pivotal role in modern manufacturing environments. Understand how these robots seamlessly integrate with human workers to enhance efficiency and productivity on the factory floor

• Enhancing Safety and Productivity: Discover how Cobots are equipped with advanced safety features, including sensors and force-limiting technology, to ensure a secure working environment. Learn how this enhanced safety allows for increased productivity as Cobots and human workers collaborate on various tasks

• Embracing Flexibility and Adaptability: Witness the versatility of Cobots as they adapt to evolving production demands. Explore their flexible nature and ease of programmability, enabling quick reconfiguration to meet changing workflow requirements without disruption

• Optimizing Task Performance: Gain insights into the diverse range of tasks that Cobots excel at, from assembly and material handling to inspection and packaging. Understand how Cobots optimize task performance, leading to streamlined production processes and improved operational efficiency

• Driving Innovation and Efficiency: Uncover the transformative impact of Cobots on manufacturing operations, driving innovation and efficiency across industries. Learn how embracing Cobots revolutionizes traditional manufacturing practices, empowering businesses to stay competitive in today’s dynamic market landscape

Chairs Closing Remarks

All Attendee Evening Drink Reception