CWM Summit Day One

Manufacturers often struggle to scale digital tools because sites operate with different processes, data structures, and levels of maturity. Standardizing frontline workflows creates the foundation for consistent execution, faster adoption, and reliable data across the network. This session explores practical ways to unify processes while preserving local flexibility, enabling teams to deploy digital tools faster, reduce variation, and build a repeatable model for multi site transformation.

• Creating a common workflow framework that supports consistent execution while allowing for site level adaptation

• Reducing deployment time by aligning processes, data structures and governance across plants

• Improving adoption by giving frontline teams clear, intuitive and repeatable digital workflows

• Strengthening operational visibility by generating comparable data across diverse sites and value streams

Manufacturers are facing rising labor costs, variable demand, and increasing pressure to run leaner operations. Traditional scheduling cannot keep pace with real time changes on the plant floor, leading to staffing mismatches and avoidable downtime. This session explores how AI driven scheduling uses live data to anticipate demand, allocate skills, and optimize coverage, improving labor efficiency, workforce utilization, and overall operational resilience.

• Aligning staffing levels with real time production demand to reduce overtime, idle time and labor waste

• Using AI to match skills, certifications and availability to the tasks that need them most

• Increasing workforce flexibility by dynamically adjusting schedules as conditions change

• Improving operational performance by ensuring the right people are in the right place at the right time

Manufacturers are under pressure to reduce rework, eliminate errors, and improve coordination across operations, yet many still rely on fragmented tools and manual processes that slow teams down. Enterprise work management platforms are emerging as a critical enabler, connecting people, data and workflows so frontline teams can execute with clarity and confidence. This panel explores how leading manufacturers are standardizing work, improving collaboration, and using AI enabled work management to drive consistency, accountability and real operational impact across plants and functions.

• Creating a unified work management backbone that standardizes tasks, handoffs and accountability across operations

• Using AI enabled workflows, digital instructions and real time visibility to reduce human error and improve decision quality

• Strengthening collaboration between operations, maintenance, engineering and quality through connected processes and shared context

• Building adoption and capability so work management tools become part of standard work and deliver measurable performance improvements

Travis Prior

Associate Director, SAP ERP Project Mgt, Interiors
Collins Aerospace

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Amazon Prime Air is building one of the world's most advanced autonomous delivery networks, where reliability and safety depend on a highly distributed drone fleet. This session explores how predictive maintenance is embedded across the ecosystem, from onboard diagnostics to fleet level analytics, to reduce downtime, extend asset life, and keep every aircraft mission ready.

Anitha Latha Kpau

Director of Quality
Amazon

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Maintenance teams are under pressure to work more safely, more consistently, and with greater accuracy across a wide range of assets. Yet much of the knowledge required for effective reliability centered maintenance still lives in the heads of experienced technicians or in outdated documents. This case study shows how digital work instructions capture tribal knowledge, structure complex tasks into clear workflows, and standardize procedures across the asset portfolio.  

• Capturing tribal knowledge to deliver next generation maintenance

• Transforming real work into structured digital work instructions with AI

• Standardizing inspection, setup, changeover, and maintenance procedures across your asset portfolio

• Delivering guidance matched to the needs of each worker and boosting on-the-job learning opportunities

Manufacturers are redefining the role of the frontline as AI, data, and connected systems transform asset intensive operations. Instead of reacting to failures, frontline teams are being equipped to make proactive, insight driven decisions that reduce variability and strengthen execution across a changing workforce. Success now depends on targeted upskilling, and building digital literacy so workers can interpret analytics, trust predictive insights, and collaborate confidently with intelligent systems. This panel explores how organizations are embedding these capabilities into daily routines to unlock a more predictive, resilient, and high performance frontline.

• How AI, data, and connected systems are transforming asset-intensive operations—shifting frontline workers from reactive maintenance to proactive, insight-driven decision-making

• Reducing site variability and embedding digital tools into daily routines to ensure consistent execution across a changing and high turnover workforce

• Upskilling frontline teams through targeted craft training, digital literacy development, stronger contractor leadership and dedicated change management

• Building trust in ai, predictive insights and digital workflows through cross functional communication and support

• Upskilling teams to interpret analytics, anticipate failures, and collaborate with digital systems, enabling predictive maintenance over reactive fixes

Chris Rodgers

Vice President of Operational Excellence
INX International Ink Co.

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Derreck Keith

Vice President, Advanced Product Development , HD Engines
Power Solutions International

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Destaco is transforming its manufacturing operations by replacing paper based procedures and tribal knowledge with a modern, mobile first digital work instruction platform. This initiative enables frontline teams to access clear, visual, step by step guidance directly at the point of work, improving consistency, reducing downtime, and accelerating workforce readiness. Jeff Clark will share how Destaco deployed the solution across its operations, the change management approach behind the rollout, and the measurable impact on quality, training, and operational performance.

• Accelerated onboarding and upskilling by giving new operators instant access to intuitive, visual, step by step instructions, reducing reliance on shadowing and expert availability.

• Improved first time right performance through standardized, easy to follow digital procedures that reduce variation and eliminate outdated paper instructions.

• Reduced troubleshooting and repair time by enabling operators to quickly access contextual guidance and equipment specific procedures at the point of use.

• Captured and preserved critical tribal knowledge by converting expert demonstrations and legacy documents into structured, digital workflows accessible across all sites.

• Increased operational agility by enabling rapid updates to procedures, ensuring teams always work from the latest version without manual distribution or reprinting.

Jeff Clark

Global Director of Operational Excellence & Quality NA
Destaco.

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Frontline teams are under pressure to work faster, with fewer errors, and with greater consistency across shifts and sites. Traditional work instructions often cannot keep pace with rising complexity, leading to variation, rework, and lost productivity. This session explores how AI powered digital instructions deliver real time, contextual, step by step guidance that improves accuracy, reduces training time, and drives measurable productivity gains across operations.

Manufacturers are shifting from paper and tribal knowledge to digital work instructions that capture expertise, personalize upskilling, and strengthen frontline performance. The real challenge is driving trust and daily use, equipping supervisors to lead the change, and ensuring experienced workers' knowledge is captured and embedded. As organizations scale across sites, they must measure adoption, overcome cultural and operational barriers, and enhance instructions with tools like augmented reality to reduce errors and accelerate training.

• How do you get frontline workers to trust and actually use digital instructions, especially when they're used to paper or tribal knowledge?

• What Change Management strategies did you put in place to ensure successful user adoption?

• How are you capturing the tribal knowledge and expertise of your most experienced workers and integrating that knowledge into Digital Work Instructions?

• What have you found to be the biggest barrier when scaling digital work instructions across multiple sites, and how did you overcome it?

• How do you measure adoption and ensure digital instructions are actually being used on the frontline?

Paul Koschnitzke

Vice President of Digital Manufacturing
Avantor

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AI assisted coding is reshaping how fast manufacturers can design, deploy, and scale digital solutions. In this session, Samik Mody shares how his team is using AI driven development to bypass long vendor timelines, build tools tailored precisely to existing processes, and deliver value in days, not months. Through real case studies in asset management and track and trace, he outlines what it takes to make internal development scalable, secure, and sustainable while empowering a broader workforce to build and innovate.

• Delivering manufacturing solutions 3–5x faster with AI assisted development

• Asset optimization and end to end track & trace

• Expanding the builder community while maintaining governance & scalability

• Driving workforce adoption through hyper tailored, user led design

• Data readiness, single pane of glass & device strategy

Samik Mody

Director of Information Technology, Manufacturing & Maintenance Systems
E & J Gallo Winery

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Bhupinder Gill

Sr. Technical Product Manager
E&J Gallo Winery

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Manufacturers have invested in predictive analytics, but teams often lack the root cause clarity needed to act with confidence. Causal AI reveals the true drivers behind performance, quality, and reliability issues, enabling faster, more accurate decisions. This session shows how causal models build trust in AI insights and turn complex operations into clear, actionable guidance for the plant floor.

• Identifying the real drivers behind performance and quality issues to support faster, more confident decisions

• Reducing trial and error problem solving by showing which interventions will have the greatest impact

• Improving frontline adoption of AI by providing transparent, explainable insights rather than black box predictions

• Strengthening operational performance by moving from predictive alerts to actionable, cause driven recommendations

AI Vision is rapidly reshaping inspection and quality control by moving manufacturers beyond manual checks and isolated hazard detection toward continuous, scalable, and highly accurate visual intelligence. As automotive and asset intensive operations push for zero defect performance, AI Vision is becoming a core enabler of consistent execution, faster root cause identification, and real time decision making on the line. This panel brings together leaders who are embedding AI powered inspection into daily workflows, reducing variability across sites, and building the trust, skills, and change readiness needed for frontline teams to adopt and rely on intelligent visual systems.

• How AI Vision is improving defect detection accuracy, reducing false positives, and enabling real time quality decisions at scale

• Strategies for integrating AI Vision into existing inspection workflows without slowing production or overwhelming frontline teams

• Approaches to capturing expert knowledge and training AI models to recognize complex defects, edge cases, and evolving product variations

• How organizations are building trust in AI driven inspection through transparency, cross functional communication, and frontline engagement

• Lessons learned from scaling AI Vision across multiple plants, including data governance, model retraining, and change management practices

Justin Nhan

Digital Transformation Lead & AI Divisional Lead
BASF

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Peterson Lindo

Technical Planning Innovation & Digitalization Lead
BMW

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Maria Ruuiz

Member, Women's Automotive Network and Former Manufacturing Engineer
Ford Motor Company

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As manufacturing complexity rises alongside an accelerating retirement cliff, traditional training completion metrics no longer guarantee on-the-floor operational readiness. In this session, we break down how leading manufacturers are moving past static spreadsheets and LMS "check-the-box" tracking to embrace dynamic skills intelligence. Attendees will learn how to build a unified workforce capability layer that connects frontline validation with real-time operational needs. By bridging immediate compliance assurance with structured career advancement, organizations can eliminate costly deployment bottlenecks, mitigate shift-start coverage chaos, and protect production quality across all lines.

• Moving Beyond the "Completion Clicks" Trap: Why relying on course completion data leaves operations blind to actual on-the-floor capability, and how to establish objective validation standards that prove an operator is safe to work.
• Connecting Skills to the Shift Schedule: How mapping live competency data directly to production requirements eliminates emergency call-off scrambling and prevents the safety risks of assigning unqualified workers to critical lines.
• Bridging Assurance and Advancement: A framework for using localized skill gaps to build clear development pathways, improving hourly retention by showing workers a visible track for growth before they look elsewhere.
• Data-Driven Capacity Planning: How giving plant leadership and supervisors real-time visibility into the plant's true skill depth transforms workforce forecasting from a spreadsheet guessing game into a predictable operational strategy.

Ryan Myers

Product Owner/Data Scientist
Kahuna Workforce Solutions

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United Airlines has built an integrated real time operations platform that unifies frontline workers command center teams and automated AI agents around a single operational picture. The in house system consolidates IoT signals, event data, computer vision and predictive analytics to help teams make faster and more accurate decisions. This session explores how United designed deployed and scaled this capability across airports to improve workforce alignment reduce delays strengthen customer communication and enable a new level of operational orchestration that manufacturing leaders can learn from.

• Deliver real time operational visibility through a single pane of glass by integrating IoT and operational systems for every persona from gate agents to command center leaders

• Use predictive intelligence to anticipate delays and trigger coordinated action across customer channels ramp teams crew scheduling and downstream operations

• Automate customer and workforce communication with GenAI to reduce manual effort improve message quality and ensure consistent updates across mobile apps displays and operational teams

• Enable cross functional collaboration with AI supported workflows that help frontline teams baggage catering cleaning gate agents and corporate operations coordinate in real time

• Scale adoption through a structured frontline first change management model that engages super users trains local champions rolls out by airport and maintains continuous feedback loops

Abhi Gummakonda

Senior Manager IT Airport Services
United Airlines

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Connected worker programs are evolving from simple digital tools into fully integrated ecosystems that enhance production, safety, and workforce capability. As manufacturers face growing complexity and a changing labor market, connected technologies are becoming essential for attracting new talent, supporting real time problem solving, and enabling on the job upskilling. This session explores how modern devices, data flows, and 5G enabled environments are transforming frontline work, giving employees the information, guidance, and control they need to operate more efficiently and safely while preparing the workforce for increasingly advanced machinery and automated systems.

• How can connected worker initiatives improve production and safety?

• How do connected technologies help attract and retain new talent?

• What is the impact of digital devices on real-time problem-solving and upskilling on the job?

• How can the utilization of 5G-enabled device ecosystems enable a shift from basic machine operations to advanced, integrated machinery control?

Michael Weller

Global Head of Manufacturing Practice
Verizon Business

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Dana is modernizing its global manufacturing operations by building a unified MES and data architecture that connects machines, people, and processes across multiple plants. By integrating real time machine data, automated SPC analytics, predictive maintenance logic, and frontline communication tools, Dana is creating a scalable digital foundation that improves reliability, accelerates problem solving, and reduces manual effort. This session explores how the team is layering AI, MES, and connected worker technologies to deliver measurable operational impact while preparing for the next phase of intelligent manufacturing.

• Unlock real time visibility by connecting machines, MES, and enterprise systems

• Strengthen predictive maintenance with automated downtime insights and machine level diagnostics

• Improve quality and reduce engineering workload with AI driven SPC across value streams

• Capture frontline "soft data" to accelerate problem solving and close the loop on downtime

• Build a scalable digital foundation that supports standard work, cycle time accuracy, and future AI use cases

William Bill Hornsby

Global Vice President, Operational Excellence
Dana

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Manufacturers are accelerating AI adoption, yet many initiatives stall because the operational foundation is not ready: work is not fully digitized, execution data is inconsistent, and machine signals are disconnected from frontline action. This session outlines a practical, real world path to AI that begins with standardized work and trustworthy data, then builds toward connected assets and automated decision flows.

• Establish a reliable operating dataset by digitizing and standardizing frontline work across assets, shifts, and sites

• Strengthen asset context and governance to ensure machine, maintenance, and execution data can be trusted for AI driven decisions

• Connect PLC, SCADA, and sensor data to frontline workflows to close the loop between equipment signals and real operational action

• Automate prioritization and response by activating AI to turn alerts into targeted work that improves uptime, throughput, and labor efficiency

• Accelerate progress with a clear sequencing model and early use cases that build credibility while avoiding multi quarter integration delays.

Nick Haase

Co-Founder
MaintainX

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Bayer is modernizing its manufacturing network by shifting from tribal knowledge and inconsistent workflows to a standardized, system driven planning and scheduling model. After rolling out a new scheduling solution across two major sites, the team uncovered critical insights about change management, site engagement, and the importance of reliable, repeatable workflows. This session explores how a structured scheduling foundation enables better decision making, clearer visibility into true process costs, and a pathway to continuous improvement across the network.

• Build a consistent, reliable scheduling workflow that replaces undocumented assumptions and tribal knowledge with validated, data driven processes

• Engage plant teams early and continuously to ensure ownership, adoption, and readiness for new system driven ways of working

• Use standardized workflows to reveal true process costs, identify bottlenecks, and uncover improvement opportunities that were previously invisible

• Apply lessons learned from the first site rollout to accelerate success at subsequent sites and create a repeatable deployment model

• Position planning and scheduling as a foundation for broader digital transformation, including AI enabled optimization and future connected worker initiatives

Prasanthi Muddhana

Head of Digital and Process Enablement Unit
Bayer

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Maintenance teams are under increasing pressure as experienced technicians retire and newer workers step into more complex roles with less hands on knowledge. Predictive AI diagnostics are reshaping maintenance execution by capturing tribal knowledge, analyzing historical data, and giving frontline teams real time guidance to troubleshoot issues with greater speed and accuracy. This session explores how AI driven insights support faster root cause analysis, improve first time right performance, and help organizations build a more capable, resilient maintenance workforce.

• Addressing the challenge of a retiring workforce: how to leverage tribal knowledge and historical data to upskill new workers

• Empowering frontline workers with AI Diagnostics to achieve faster troubleshooting

• Leveraging agentic AI for root cause analysis and improving first-time-right fixes

Mark Fosdike

CEO and Co-Founder
Datch

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Pella's make to order environment demands precision, speed, and flawless coordination across facilities. Haley will share how her engineering and product teams are designing and scaling quality applications that eliminate rework, reduce waste, and give frontline teams real time clarity. Her session highlights the practical, user centric digital tools that are strengthening quality, flow, and decision making across complex manufacturing operations.

• Developing internal quality apps that directly solve manufacturing problems and reduce rework

• Creating "ready to build" visibility to prevent downstream disruption and improve flow

• Designing tools that scale across facilities with different processes and product complexities

• Ensuring adoption through strong UX, mobile first design, and manufacturing savvy teams

• Reducing waste and improving throughput with real time status across interconnected plants

Haley Berland

Intelligent Operations Product Owner/Engr. Team Leader
Pella

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Manufacturers are facing unprecedented workforce disruption, skills gaps, and operational variability. Traditional digitization alone is no longer enough. This session explores how Augmentir's AI native Connected Worker Platform, powered by Industrial AI Agents, Generative AI, and integrated digital workflows, creates a unified "single pane of glass" for frontline operations. Attendees will learn how leading manufacturers are accelerating onboarding, improving quality and safety, and enabling every worker to perform at their best through adaptive, personalized, AI driven support.

Dave Landreth

Vice President, Customer Strategy
Augmentir

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Marathon Petroleum is laying the groundwork for AI powered technology with a transformational program designed to standardize maintenance operations. With a focus on data quality, system integration, and process consistency, this initiative is enabling scalable AI use cases across the full IPSEC lifecycle (Identify, Plan, Schedule, Execute, Close). As Dan shares, this foundational work is critical, especially in light of a recent MIT study showing that 95% of AI initiatives deliver little to no measurable value. This session explores how Marathon is building the digital and data infrastructure needed to ensure AI delivers real operational impact and how they're actively exploring AI use cases that support predictive maintenance, intelligent scheduling, and frontline decision-making.

• Unifying maintenance processes across pipelines, terminals, and logistics, creating a consistent data layer that supports AI integration and long-term operational visibility

• How AI agents are being designed to support complex planning and scheduling decisions, factoring in asset priority, workforce availability, geospatial constraints, and material readiness

• Preparing for future use cases, including predictive modelling for asset health, computer vision for leak detection, and intelligent agents that assist with troubleshooting and parts ordering

• Generating a rich dataset across the full maintenance lifecycle, enabling continuous improvement and reshaping how operational excellence is measured and achieved

Daniel Byrne

Senior Director of Digital Transformation
Marathon Petroleum

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Manufacturers need to respond faster to changing production demands, workforce shortages, and increasing operational complexity. This session explores how AI-powered skills visibility helps organizations match the right people to the right tasks in real time, improving agility, productivity, and workforce effectiveness across the shop floor.

• Defining and managing skills requirements across roles, tasks, and operations
• Integrating skills visibility with HR, learning, and operational systems to create a connected workforce ecosystemBalancing global standardization with local operational requirements and exceptions
• Using AI to improve skills visibility, identify gaps, and support future workforce planning
• Reducing dependency on tribal knowledge while accelerating onboarding and cross-training
• Building a connected workforce strategy that supports both operational performance and employee development

Rick van Echtelt

CEO and Founder
AG5

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Kimberly Clark is modernizing MES across 75 plants through a global standardization program designed to unify processes, strengthen data foundations, and improve frontline adoption. In this case study, Suraj Sriram shares how his team accelerated deployment in North America, balanced standardization with site level needs, and built the cross functional engagement required to scale digital manufacturing systems effectively.

• Standardizing MES at scale through an 80/20 global template and a process family rollout model

• Sustaining performance with a dedicated MES specialist network, providing on site training, troubleshooting

• Digitizing frontline routines with mobile checklists and digital data capture to improve accuracy, compliance, and operator ownership

• Laying the groundwork for AI enabled operations by piloting operator support use cases that reduce dependency on stretched support teams and improve decision making

Suraj Sriram

Digital Manufacturing Leader
Kimberly-Clark

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Manufacturers are accelerating their use of AI, yet many still struggle with fragmented data, disconnected systems and limited visibility across operations. True value comes when AI is embedded into core business processes and powered by a unified, trusted data foundation. This session explores how organizations are activating contextualized data, automating decision making and empowering frontline teams with real time insights to improve reliability, optimize production and drive measurable business outcomes.

• Create a unified, trusted data layer that connects ERP, MES, supply chain and operational systems

• Embed AI directly into daily workflows to improve decision making and operational efficiency

• Accelerate predictive maintenance, quality and production optimization with integrated analytics and machine learning

• Empower the workforce with role based insights and intelligent guidance

• Modernize the digital manufacturing landscape with scalable, secure and enterprise grade AI capabilities

Andy Hancock

Global Vice President of the Domain Advisory, SAP Supply Chain Management
SAP

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Sabert's transition to CMMS delivered one of the platform's strongest adoption stories, driven by a disciplined change management approach and deep workforce engagement. Emily Hebert, Senior Director of Operational Excellence, led the initiative in partnership with machine reliability leadership, reducing unplanned downtime and building a durable culture of digital ownership. This session outlines the practical steps, leadership behaviors, and cross site strategies that enabled Sabert to achieve lasting operational impact.

• Achieved a reduction in unplanned downtime from 15% to 9% within two years, driven by structured change management and frontline involvement.

• Built sustained user adoption by engaging the workforce early, involving them in vendor selection, and creating a clear, multi channel communication plan

• Secured full leadership buy in at every level, ensuring plant managers and directors actively championed the rollout and reinforced daily usage.

• Strengthened cross site consistency through pilot site champions, peer to peer training, and structured feedback loops with Innovapptive to rapidly close system gaps.

• Established a continuous improvement rhythm with weekly check ins, feedback surveys, and rapid vendor response, ensuring the system remained easy and valuable for the workforce.

Emily Hebert

Senior Director of Operational Excellence
Sabert

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Manufacturers are under increasing pressure to streamline operations, reduce costs, and respond faster to market volatility. Modern data analytics, powered by unified cloud platforms, is enabling leaders to turn IoT, OT, and enterprise data into real time insights that improve quality, strengthen supply chain resilience, and optimize production. By centralizing diverse data sources and applying advanced analytics and AI, manufacturers can uncover hidden efficiencies, predict disruptions, and make smarter decisions across the value chain. 

• Improve operational reliability with predictive maintenance models that reduce unplanned downtime and increase productivity.

• Strengthen supply chain performance through integrated, real time data that anticipates disruptions and supports faster decision making.

• Enhance production quality by analyzing IoT and sensor data to identify defects earlier and optimize processes.

• Increase end to end visibility by unifying IT, OT, and IoT data into a single platform that accelerates Industry 4.0 initiatives.

Frontline workers often struggle with fragmented systems, multiple logins and inconsistent workflows that slow execution and increase the risk of error. By consolidating production, quality and traceability tasks into a single, intuitive interface, manufacturers can simplify the operator experience and dramatically improve data accuracy, compliance and productivity. In this session, Pareshkumar Hotchandani shares how his organization is creating a unified frontline environment where workers complete all required actions through one screen. He will outline the integration strategy, data architecture and change management approach behind this transformation, and how it is enabling faster adoption and more reliable operations across global sites.

· Creating a one screen operator experience that eliminates system hopping and reduces cognitive load

· Integrating production, quality and enterprise systems behind the scenes

· Empowering frontline teams to help design and maintain digital workflows

· Improving data accuracy and speed by replacing manual paperwork with automated digital capture

· Scaling a unified interface across global sites with different processes, regulations and levels of maturity

Pareshkumar Hotchandani

Global Staff Engineer/Site Lead Operational Technology
Smith+Nephew

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