| Copyright 2014 Simio LLC | All rights reserved. 1 Executing Simulation Experiments in the Cloud C. Dennis Pegden, CEO Simio LLC

| Copyright 2014 Simio LLC | All rights reserved. 2 Cloud computing  Avoid infrastructure costs.  Focus on value added activities.  Shorten development time.  Less maintenance, easier to manage.  Scale resources to changing demand.

| Copyright 2014 Simio LLC | All rights reserved. 3 Cloud Manufacturing  Cloud-based manufacturing paradigm based on Internet of Things (IoT) and virtualized/service oriented technologies.  Encompasses the life cycle of a product – design, simulation, production, test, maintenance.  Cloud-based simulation for both facility design and production planning/scheduling.

| Copyright 2014 Simio LLC | All rights reserved. 4 Cloud Computing Drivers 1. Mobile and shared information. 2. Scalable demand. 3. Scalable (parallel) computation. Most applications leverage 1 and 2. Simulation applications leverage all three.

| Copyright 2014 Simio LLC | All rights reserved. 5 Facility Design  Allow 3D animated simulation models to be built and run in the cloud for improving system design.  Model building  Data integration  Animation  Experimentation

| Copyright 2014 Simio LLC | All rights reserved. 6 Example: Facility Design

| Copyright 2014 Simio LLC | All rights reserved. 7 Experimentation  Models are used to compare alternative designs, or optimize design parameters.  Randomness requires that each scenario is replicated.  During experimentation animation is not required.  Multiple processes allow scenarios and replications to be run in parallel.

| Copyright 2014 Simio LLC | All rights reserved. 8 Cloud Challenges/Opportunities  Cloud-based 3D animation environments don’t exist.  Model data is dispersed and not easily accessed.  Experiments can be executed in parallel. Data interfacing is the highest priority issue limiting the vision.

| Copyright 2014 Simio LLC | All rights reserved. 9 Working within the existing limitations  Models are built using desktop software.  Data is first integrated into the model – the project (model + data) is then uploaded to the cloud.  Experimentation can leverage the full scalable processing power of the cloud (e.g. 25 replications of 10 scenarios simultaneously executed).

| Copyright 2014 Simio LLC | All rights reserved. 10 Planning and Scheduling  Allow simulation-based scheduling systems to be executed in the cloud, and the results deployed across the enterprise.  Deterministic model used to generate schedule.  Interface to ERP/MES data.  Evaluate alternative scenarios (expediting jobs, overtime, etc.).  Analyze delivery risks by replicating the schedule with uncertainty and unplanned events.  Publish the selected plan to mobile devices for execution.

| Copyright 2014 Simio LLC | All rights reserved. 11 Example: Planning and Scheduling

| Copyright 2014 Simio LLC | All rights reserved. 12 Risk Analysis  Deterministic plans assume away uncertainty/unplanned events – they provide optimistic results.  By replicating the plan with variation/uncertainty added into the model we can estimate schedule risk.  Multiple processes allow replications for risk analysis to be executed in parallel.

| Copyright 2014 Simio LLC | All rights reserved. 13 Cloud Challenges/Opportunities  Cloud-based modeling environments don’t exist.  Model data is dispersed and not easily accessed.  Experiments can be executed in parallel, providing quick comparisons of alternative schedules and risk analysis. Data interfacing is the highest priority issue limiting the vision.

| Copyright 2014 Simio LLC | All rights reserved. 14 Working within the existing limitations  Models are built using desktop software.  Data is first integrated with model – the project (model + data) is then uploaded to the cloud.  Experimentation can leverage the full scalable processing power of the cloud (e.g. 25 replications of 10 scenarios simultaneously executed).  Risk analysis can leverage the full scalable processing power of the cloud.

| Copyright 2014 Simio LLC | All rights reserved. 15 Top Priority is Data Integration  Cloud manufacturing solutions will initially be hybrid environments (e.g. ERP cloud, MES on premise).  Solutions must interface to dispersed data – some on premise – some in the cloud.  Data integration between cloud and on premise components (e.g. ERP, MES, IoT, custom data sources) needs to be simple and seamless.