Discover Our Business
Simulation
Wire-Frame of Gear and Manufacturing Site

Manufacturing

Is a new Industrial Revolution taking place? Quite possibly, yes. New tools to build smarter, leaner factories and explore innovative new products, materials, and techniques at a lower cost are emerging. Additive manufacturing, next-generation electronics, and advances in materials are upending the traditional manufacturing floor. How do you adjust?

Digital technology - simulation in particular - affords engineers and manufacturing professionals the ability to try out new technology and accelerate manufacturing innovation in novel ways never thought possible before.

complete-factory-models

Complete Factory Models

A huge model for DTE Energy that covered field, shop, office, and supply chain functions relating to electric metering equipment was built in ExtendSim in just 6 short weeks. Management was wowed by...

read more

production-lines

Production Lines

Procter & Gamble (P&G) has used ExtendSim to "model all product lines - from soap to nuts" for design of equipment and production lines, scheduling, commerce, quality, etc. The models they build are used...

read more

reliability-engineering

Reliability Engineering

Dow Chemical Company performs reliability modeling in ExtendSim to identify and understand the impact of different failures on overall production capabilities in chemical plants. The model is used...

read more

sales-tool

Sales Tool

A major medical laboratory automation equipment producer sends its sales forces out to client sites with ExtendSim models to customize equipment for customers so the customer can see the proposed...

read more

ExtendSim in Manufacturing

  • Inventory and resource management.
  • Managing Six Sigma/Lean initiatives.
  • Scheduling and capacity planning.
  • Procedure evaluation.
  • Monte Carlo modeling.
  • Capital investment analysis.
  • Throughput and cycle time.
  • Predict operational characteristics of projects.
  • Measure average wait time and length of the queue.
  • Batch and campaign sizes vs one-piece flow.
  • Line balancing and routing changes.
  • Speed prediction of a new motor in a robotic vehicle system checking its performance under varying conditions
  • Analysis of bottlenecks in a seven-step manufacturing process.

ExtendSim in Manufacturing

  • Inventory and resource management.
  • Managing Six Sigma/Lean initiatives.
  • Scheduling and capacity planning.
  • Procedure evaluation.
  • Monte Carlo modeling.
  • Capital investment analysis.
  • Throughput and cycle time.
  • Predict operational characteristics of projects.
  • Measure average wait time and length of the queue.
  • Batch and campaign sizes vs one-piece flow.
  • Line balancing and routing changes.
  • Speed prediction of a new motor in a robotic vehicle system checking its performance under varying conditions
  • Analysis of bottlenecks in a seven-step manufacturing process.

Who is using ExtendSim in Manufacturing

  • For over two decades, P&G and Los Alamos National Laboratory (LANL) have collaborated in reliability engineering to create a proprietary set of tools (which includes ExtendSim) to understand the dynamics driving the production systems and provide solutions to accelerate throughput and productivity results.Reliability and throughput have increased 30 to 100% while scrap has been reduced by 20 to 50%.
  • Grayrock & Associates LLC helped executives at an injection modeling plant determine if more equipment and an expanded space would be needed to meet increased production demands. The model substantiated that throughput could be increased by 25% without plant expansion or capital expenditures.
  • Printing equipment manufacturer Polar Mohr developed a model that shows the productivity of their machines in a variety of applications. Sales engineers use this ExtendSim model to demonstrate the advantage of their equipment to their customers.
  • Johnson & Johnson commissioned the OpStat Group to create a simulation model which would examine current operations and develop solutions for the future for one of its large pharmaceutical plants. The model allowed the company to pre-test process changes and assist in the selection of techniques as part of a Lean Six Sigma program. The scope evolved from improvement and capacity projects to becoming integral to the ongoing planning and management process. Ultimately significant benefits ensued -- better utilization of personnel, accelerated delivery of value-added projects, and improved accuracy and timeliness of planning information -- allowing plant and supply chain management to evaluate options for sourcing and capacity within the plant and across the supply chain.
  • A Fortune 100 Consumer Products Company saved $1 billion across its operations by improving manufacturing reliability. Thus, allowing the company to introduce technology at a faster pace.
  • Working as a team, Crutchfield Corporation, a major consumer electronics catalog and Internet retailer, and Rust Management Technology used ExtendSim combined with ExpertFit to develop and validate a distribution center process simulation using Six Sigma techniques. Using insights developed through the simulation, Crutchfield Corporation estimates that it will save 15 to 20 times the cost of the project in the first year after deployment.
  • An automotive equipment manufacturer optimizes the design of its suspension systems by comparing a model’s simulated results to real-time data transmitted by sensors on automobiles.
  • A New Zealand pulp and paper mill models their integrated pulp mill, recycle facility, and sack kraft machine to determine the optimum mix of products and grades for specific economic conditions. This mill now boasts bleached softwood kraft production costs in the bottom quartile worldwide.
  • A polyethylene producer looked to determine the size of the intermediate tank between the ethylene production and its later polymerization. The tank allowed to free the two sectors of the production when one of them stopped for lack of supply or raw materials or flaws in the equipment. Incremental sizes of the tank allowed a bigger independence between the processes with a concrete increase of the PE production; this trade-off (size/cost of the tank vs. expected incremental outcome) was subject to scrutiny using simulation, allowing to feed a complementary economic analysis.
  • An industrial company wanted to determine the optimal use of a worker serving a pool of 6 (six) wiring machines. The purpose of the study was to assign more tasks to the same person because the demand of attention of machines did not consume the entire person's available time. Surprisingly, the recommendation coming from the simulation model was to add a second worker to the same sector. This would result in a very low use of manpower, but a very important increment of the machines' output due to the interference of the flaws of the different machines along time, causing two or more machines were stopped waiting of the attention of the crew.
  • IBM Global Services Australia built a print distribution model in ExtendSim to determine delivery times, resource requirements, duty rosters, and capacity to meet Service Level Agreements during Summer Olympic games.
  • $100 million annual savings by an international paper manufacturer who used ExtendSim to improve the effectiveness of their capital investments.
  • A tobacco manufacturing plant in Augustow, Poland built an ExtendSim model to support the triplication of production volume within a five year time period as an answer to the entrance of Poland in the European Economic Community.
  • ExtendSim has been used to model wing production for 737s.
  • PCB and semiconductor facilities.
  • Consumer product manufacturers.
  • Aerospace operations.

Who is using ExtendSim in Manufacturing

  • For over two decades, P&G and Los Alamos National Laboratory (LANL) have collaborated in reliability engineering to create a proprietary set of tools (which includes ExtendSim) to understand the dynamics driving the production systems and provide solutions to accelerate throughput and productivity results.Reliability and throughput have increased 30 to 100% while scrap has been reduced by 20 to 50%.
  • Grayrock & Associates LLC helped executives at an injection modeling plant determine if more equipment and an expanded space would be needed to meet increased production demands. The model substantiated that throughput could be increased by 25% without plant expansion or capital expenditures.
  • Printing equipment manufacturer Polar Mohr developed a model that shows the productivity of their machines in a variety of applications. Sales engineers use this ExtendSim model to demonstrate the advantage of their equipment to their customers.
  • Johnson & Johnson commissioned the OpStat Group to create a simulation model which would examine current operations and develop solutions for the future for one of its large pharmaceutical plants. The model allowed the company to pre-test process changes and assist in the selection of techniques as part of a Lean Six Sigma program. The scope evolved from improvement and capacity projects to becoming integral to the ongoing planning and management process. Ultimately significant benefits ensued -- better utilization of personnel, accelerated delivery of value-added projects, and improved accuracy and timeliness of planning information -- allowing plant and supply chain management to evaluate options for sourcing and capacity within the plant and across the supply chain.
  • A Fortune 100 Consumer Products Company saved $1 billion across its operations by improving manufacturing reliability. Thus, allowing the company to introduce technology at a faster pace.
  • Working as a team, Crutchfield Corporation, a major consumer electronics catalog and Internet retailer, and Rust Management Technology used ExtendSim combined with ExpertFit to develop and validate a distribution center process simulation using Six Sigma techniques. Using insights developed through the simulation, Crutchfield Corporation estimates that it will save 15 to 20 times the cost of the project in the first year after deployment.
  • An automotive equipment manufacturer optimizes the design of its suspension systems by comparing a model’s simulated results to real-time data transmitted by sensors on automobiles.
  • A New Zealand pulp and paper mill models their integrated pulp mill, recycle facility, and sack kraft machine to determine the optimum mix of products and grades for specific economic conditions. This mill now boasts bleached softwood kraft production costs in the bottom quartile worldwide.
  • A polyethylene producer looked to determine the size of the intermediate tank between the ethylene production and its later polymerization. The tank allowed to free the two sectors of the production when one of them stopped for lack of supply or raw materials or flaws in the equipment. Incremental sizes of the tank allowed a bigger independence between the processes with a concrete increase of the PE production; this trade-off (size/cost of the tank vs. expected incremental outcome) was subject to scrutiny using simulation, allowing to feed a complementary economic analysis.
  • An industrial company wanted to determine the optimal use of a worker serving a pool of 6 (six) wiring machines. The purpose of the study was to assign more tasks to the same person because the demand of attention of machines did not consume the entire person's available time. Surprisingly, the recommendation coming from the simulation model was to add a second worker to the same sector. This would result in a very low use of manpower, but a very important increment of the machines' output due to the interference of the flaws of the different machines along time, causing two or more machines were stopped waiting of the attention of the crew.
  • IBM Global Services Australia built a print distribution model in ExtendSim to determine delivery times, resource requirements, duty rosters, and capacity to meet Service Level Agreements during Summer Olympic games.
  • $100 million annual savings by an international paper manufacturer who used ExtendSim to improve the effectiveness of their capital investments.
  • A tobacco manufacturing plant in Augustow, Poland built an ExtendSim model to support the triplication of production volume within a five year time period as an answer to the entrance of Poland in the European Economic Community.
  • ExtendSim has been used to model wing production for 737s.
  • PCB and semiconductor facilities.
  • Consumer product manufacturers.
  • Aerospace operations.

Trusted by Leading Manufacturing Teams

dnv-gl
dow-chemical-company
dte-energy
los-alamos-national-laboratory

Case Studies

The implementation of a real-time RFID-based inventory management system significantly improved operational efficiency at a warehouse previously reliant on manual pallet tracking and verbal...

Packages that accurately emulate the hybrid processes that characterize food and beverage manufacturing are making simulation more than just a snazzy presentation tool for upper management. Virtual...

This paper presents a closed loop supply chain for a reusable, deteriorating tool. The tool is used in a manufacturing process on an item in a linear supply chain. A model is created for the linear...

A master thesis within mechanical engineering performed by two students has been conducted at Scania in Oskarshamn. The purpose has been to investigate if Discrete Event Simulation using ExtendSim...

This project establishes a Closed-Loop Supply Chain (CLSC) design that is analysed through a series of simulation models, aimed at defining the highest performing production control strategy, whilst...

Shipbuilding is one of the most complex existing manufacturing processes. The large number of operations necessary to produce the parts that make up a vessel coupled with the need to synchronize...

In multiproduct manufacturing systems, it is difficult to assure that an optimised setting of a pull production control strategy will be able to maintain its service level and inventory control...

Designing a casthouse for billet is a complex activity. The billet casthouse must be properly sized to optimize the metal flow, and continuously feed the homogenization shop, while bearing in mind...

Variability in production is one of the largest factors that negatively impacts construction project performance. A common construction practice to protect production systems from variability is the...

Brief introductory article discussing the key element in lean implementation: simulation. Simulation has been used successfully in factory floor improvement, inventory management, capacity analyses,...

This paper presents a case study where simulation was used to convert from a manufacturing resource planning (MRP) based push process to a demand-driven pull process in a single plant operation...

Procter & Gamble partnered with the Energy Department's Los Alamos National Laboratory (LANL) in the 1990s. LANL scientists helped P&G engineers develop simulations to improve the...

LED (Light Emitting Diode) has many excellent features as a new lighting device and has been widely used by far. The structure and light-emitting principles are introduced in this paper. The LED...

"Some years ago I walked into a PCB facility that was making very complex HDI product, but wasn’t making any money. By focusing on constraining the WIP (CONWIP), identifying and focusing on the...

Logic and assumptions used in building a simulation model of an Automated Material Handling System (AMHS) for an eight inch Wafer FAB are presented in this paper. The ExtendSim model built for this...

Videos

Gray McQuarrie, president of Grayrock & Associates, uses a discrete event model built in ExtendSim to look at issues of dealing with finite plant capacity. He also touches on design of...

The key to discrete event modeling is the construction of a flow diagram using blocks to represent the problem's operations and resources. The most common discrete event model involves the handling...