ProModel and Autodesk – Partners in Optimal Factory Design

Autodesk, the creator of AutoCAD® and Inventor® software, and ProModel have teamed up to bring you the best of both worlds of factory design and process optimization.  ProModel’s Process Simulator Autodesk Edition and ProModel Optimization Suite Autodesk Edition connect to Autodesk’s AutoCAD, Inventor, and Factory Design Utilities in order to streamline model building, process optimization and ultimately facility design.  You can get a 30-day evaluation version of both products from the Autodesk App Store

Process Simulator Autodesk Edition Eval

ProModel Optimization Suite Autodesk Edition Eval

Check out these great new Process Simulator Autodesk Edition videos:

Executive Overview – 2 min

 

Detailed Overview – 6 min


 

An Introduction to Manufacturing Process Simulation at Rose-Hulman Institute of Technology

Rose-Hulman McCormack_Jay

Dr. Jay McCormack; Rose-Hulman – Associate Professor Mechanical Engineering

I teach classes in both the mechanical engineering and engineering design programs at Rose-Hulman Institute of Technology in the areas of design and manufacturing. Rose is a small college in Terre Haute, Indiana focused on STEM. In the mechanical engineering program, one of the courses that we find differentiates our graduates is a junior level course on design for manufacturing. Instead of focusing on the sciences of manufacturing processes (which is clearly very valuable also), our course focuses on the application of design principles to facilitate the manufacturing of a given product, comparison of various manufacturing methods, and supporting design best practices related to manufacturing such as geometric dimensioning and tolerancing.

Two years ago, one member of the teaching team, the original creator of our design for manufacturing class, proposed integrating a process simulation project into the course. Our students are exposed to many manufacturing methods and work in depth with a few, but never had any exposure to manufacturing process. This is arguably appropriate content for any mechanical engineer but, a robotics minor is popular with our mechanical engineers, and many of the robotics students end up in positions related to manufacturing. Additionally, many biomedical engineers take the course and end up working as process engineers for medical device manufacturers. Therefore, the need was there for students to get a first exposure to manufacturing process and process simulation. I had some experience with process simulation more than a decade ago and experience with lean manufacturing so I was elected (appointed) by the teaching team to develop the project. I was familiar with ProModel products, but it had been a while since I used any simulation tools. I evaluated Process Simulator, a tool from ProModel that installs as a plug in to Microsoft Visio, and several other products, but found that Process Simulator allowed me to get students from zero to their first model quickly. After choosing Process Simulator and discussing the options to get the software from ProModel, I started developing the project.

Project Outcomes

My first objective was to develop the learning outcomes for the project. There were a few factors driving the learning outcomes:

  1. The students were almost exclusively novices. Virtually none of the 175 students in the course had any experience with any process simulation software, so the learning outcomes had to include low Bloom’s level items focused on both manufacturing topics and Process Simulator concepts.
  2. The design for manufacturing course itself has a number of bottlenecks involving other projects. Several hands on course projects involve specialized equipment and technician time. These projects require creative scheduling to get all students equal access to these resources in an eight-week period. Consequently, the learning outcomes and process simulation project were scoped to allow students to work in a self-directed manner with a given set of tutorial videos, feedback from their instructor, and a due dates that varied for project teams.

At the successful completion of this project, students will be able to:

  1. Define manufacturing process terms – batch, process, inventory, WIP, workstation, buffer, cycle time.
  2. Define fundamental Process Simulator concepts – entity, resource, activity, routing, arrival, setting simulation properties, batching, buffers, and priority.
  3. Apply Process Simulator to model a manufacturing process using the fundamental concepts.
  4. Redesign a manufacturing process using Process Simulator.

Even with just those basic concepts the students were able to create useful Process Simulator models of a given manufacturing process. Additionally, the model was sufficiently complex to require creative experimentation and exploration in order to make improvements.

Project Overview

The objective given to students was to use Process Simulator to model the performance of a factory, suggest improvements to the factory, and measure the impact of the improvements. Excerpts from the project description follow and a link to the complete project description is located at the end of this article.

Scenario

You are an engineer at HOBO Inc. (Hands On Bottle Opener, Inc.), producers of a line of extruded, one-handed bottle openers (The Blue Collar, Figure 1) that appeal to customers through durability, reliability, and functionality. You were on the new product development team that designed a new, beautiful, and refined one-handed bottle opener (The Executive, Figure 2) that will allow you to enter an untapped market. The new design is fabricated using an investment casting process that fits well with the geometric complexity and modest volume of production planned for the new model. Because investment casting is not part of HOBO’s core competency, you will outsource the casting. HOBO will receive a shipment of boxes of unfinished casting trees from the fabricator every morning. Each bottle opener will be sawn from the casting tree then tumbled to remove burrs and to produce better surface finish. Sawing, tumbling, and the subsequent inspection step are among our core competencies, so we plan to perform these operations in house on an existing production line. Additionally, we have two workers that are available on the day shift to be used as much as they are needed. (Note that they will not be fired if they are not used all day. We have work for them elsewhere in the factory.) 

This seems like a great opportunity to try the new process simulation software that you are evaluating for purchase. You gathered some baseline data about the operation (see the Factory Description) based on the verbal description by other engineers and managers. The information that you gathered is in the section called Baseline Factory Description.

Baseline Factory Description

There are four workstations. In order, they are:

  1. Receiving
  2. Sawing
  3. Tumbling
  4. Inspection

There are buffers to store work in process (WIP) located before sawing and before tumbling. A flowchart representing the process is shown in Figure 3. A process box for each workstation and the buffers is shown in Table 1. A more complete description of each is found after the table.

Rose-Hulman_Material Flow

Figure 3. Flow of Materials through the Baseline Factory

Deliverables

In order to earn a C Use Process Simulator software to provide a baseline estimate of net income (revenue – expenses) for the first year of operation. The Baseline Factory must follow all the process rules and procedures outlined in the Baseline Factory Description section. Write a memo summarizing the findings.
In order to earn a B Design meaningful improvements to the Baseline Factory. Describe the Improved Factory in the memo by capturing each of the suggested improvements.
In order to earn an A Use Process Simulator to model the Improved Factory. Report the improvement in yearly net income in the memo.

Details about the baseline factory are provided in subsequent sections, as is a set of tutorial videos that guide students through basic concepts. The videos are a mix of guided examples recorded by me and videos provided by ProModel.

Takeaways

This project was first developed and used in academic year 2018-2019. We were pleased with the enthusiasm that students approached the project and engaged in competition to produce the most profitable manufacturing process compared to their peers. We revised the project for 2019-2020 to include a grading scale that further encouraged exploration and a set of tutorial videos walking students through a given omelet station Process Simulator model.

All of the students received a base level exposure to process simulation, but we were pleased to see that a number of students dove deeper into manufacturing process issues. Students challenged the notion that inspection was required to wait until the last process step, unknowingly suggesting the use of quality at the source, a fundamental lean concept. Those students were able to see the positive impact of quality at the source in their Process Simulator models. Other students had insights about the impact of batch work and how batches served as mechanisms for covering root cause process issues. Those students reduced batch sizes where possible and identified the root cause problems.

The complete project description, scoring rubric, and tutorial video list is linked here. You are welcome to reuse it, modify it, make it better, and/or fix mistakes. If you do, let me know at mccormac@rose-hulman.edu. We look forward to featuring Process Simulator as part of our design for manufacturing course in future years and finding new ways to challenge students to explore manufacturing processes and process simulation.

Bio

Dr. Jay McCormack is an Associate Professor of mechanical engineering at Rose-Hulman Institute of Technology. Dr. McCormack’s teaching and professional development interests are in the areas of design and manufacturing. He teaches courses for the mechanical engineering and engineering design programs as well as the institute’s multidisciplinary design course. Before joining Rose-Hulman, Dr. McCormack was a faculty member at the University of Idaho where he worked with the state’s manufacturing extension partnership. He co-founded Pittsburgh-based CAD tool developer DesignAdvance Systems Inc. after graduating from Carnegie Mellon with a PhD in mechanical engineering.

Product Launch – Process Simulator Material Handling Edition

Aaron Nelson Product Dev. Manager Process Simulator

Aaron Nelson Product Manager

I am excited to announce the launch of the Process Simulator Material Handling Edition. This edition of Process Simulator now supports modeling material flow.

Along with the drawing environment being scaled, you now will have access to Stations, Conveyors, Path Networks and Nodes.

Image_PCS MH MFG Demo Model

Stations – A new type of activity created to enhance material handling. The station can have capacity or capacity can be turned off—designed to be used with conveyors.

  • The user can insert an on-board station into a conveyor.

pcs-station

pcs-station-properties

Conveyors – A new connector with properties to control how entities flow from activity to activity. Introducing stations in a conveyor will enhance the ability to control flow from conveyor to conveyor

  • Control speed of conveyors
  • Control distance of conveyors
  • Control orientation of entities
  • Control accumulation of entities

pcs-conveyor

pcs-conveyor-properties

Path networks – Resource movement can be added to enhance your model with travel, pick up, and deposit time.

pcs-path-networks-1

pcs-path-networks-2

Material Handling usage in a manufacturing environment is obvious, but maybe not as obvious in a Healthcare Environment, but it can be valuable there too.  One example is delivering prescriptions from the hospital pharmacy to a pick-up point on each floor, from where they would be picked up and delivered to patient rooms.

Image_PCS MH HC Demo Model

You can see additional features on the Process Simulator Material Handling Edition webpage.  You can also watch our introductory webinar on how to use this new edition on the website refresher course page

Thanks for your continued business and support.  We wish you and your family good health!  Let me know if you have any questions or comments on the material handling functionality.

Aaron

 

Visualizing your Shipyard with Shipyard AI

Shipyard AI, ProModel’s dedicated shipbuilding application, continues to evolve and develop new capabilities – With five software releases in 2019, desired improvements in shipyard capacity management, optimization, scheduling and process engineering have been realized.   In addition, there has been a heavy emphasis on improving management’s ability to visualize shipyard production at both the strategic and tactical levels, at a single glance.

Building on a Strong Foundation

Historically, Shipyard AI has provided solid data and process information in highly detailed representations.  The application has included the following key visualizations, which we’ve continued to refine and improve over the years.

The Laydown map provides a top-down view of the entire shipyard with animation showing the progress of ship construction over time.

Image_syai-visualiaztion-article-laydown-map

Capacity Utilization Package (CUP) reports visualize resource utilization over time.

Image_syai-visualiaztion-article-cup-report

The Schedule screen features a Gantt chart representation of hull construction.

Image_syai-visualiaztion-article-schedule

The Unit Template Tree report shows a hierarchical breakdown of a hull into its component grand blocks, blocks, panels, etc.

Image_syai-visualiaztion-article-unit-template-tree

New Ways of Seeing the Shipyard

A recent emphasis on developing new types of visualizations is bearing fruit. This article introduces new ways of seeing the shipyard: the strategic Milestone Chart, the more tactical Location Resource View, and an updated Map Shapes editor.

Milestone Chart

A new Milestone Chart on the Hulls screen provides a strategic management view — visualizing the production of many hulls across long periods of time in a single view.

Image_SYAI Hulls Screen With Milestone Chart Nov 2019

Location Resource View

The Location Resource View report shows unit placements over time grouped by location.

This view allows you to interface with a unit and its dependencies in a single action, reducing the time needed and the possible introduction of errors. It provides a visualization of space in the shipyard over time to help you quickly make re-planning decisions.

Image_SYAI Location Resource View Report Nov 2019

Map Shape Editor

In an upcoming release, we’ll provide a map shapes editor to allow you to quickly add and edit unit shapes.

You can assign map shapes at the unit template level to have units appear on the Laydown Map with the correct shape.

Image_SYAI Map Shape Editor

See the What’s New Shipyard AI Webpage for more details on this year’s releases.

Process Simulator and ProModel Now Integrate with AutoCAD and Inventor by Autodesk

We are very excited to announce Process Simulator Autodesk® Edition and ProModel Autodesk® Edition.  Each product integrates with Autodesk® AutoCAD® and Autodesk® Inventor® to provide you a more valuable manufacturing plant design and process improvement capability.

For more information about Process Simulator Autodesk Edition, including videos, a downloadable pdf, and a 30-day evaluation copy go to the Process Simulator Autodesk Edition webpage.

For more information about ProModel Autodesk Edition, including videos, a downloadable pdf, and a 30-day evaluation copy go to the ProModel Autodesk Edition webpage.

If you are at the Autodesk University event this week (11/19-11/21) in Las Vegas stop by booth MFG210 to get a live demo and talk to our team.

Predictive Variables, Artificial Neural Networks and Discrete Event Simulation in Manufacturing

Rebecca Santos

Rebecca Santos ProModel Tech Support Engineer

During my Master’s program at BYU, I worked with a team to complete my thesis.  The work turned into a published article by the International Journal of Modelling and Simulation!  Since I work for ProModel, it’s only appropriate that I share it with my fellow simulation enthusiasts.  Please let me know what you think by commenting below.

Discrete event simulation (DES) is a powerful tool that can help users make better decisions. Over the years tools such as ProModel and Process Simulator have been developed to simplify the application of simulation, decreasing the learning curve and increasing its use. One of the advantages of simulation is that it is able to create lots of data with valuable information. However, the data analysis process can be challenging and relevant information may not be fully analyzed.

Observing the opportunity to more fully learn from the data, we decided to use data mining algorithms to help in the data analysis process, and more than that, to guide the modeler to the variables that most impact the outcome of the system being modeled.

The data mining algorithm picked was Artificial Neural Networks (ANNs) which has been good at learning from the data and making accurate predictions, according to the scientific literature. We applied ANNs to the data generated by the simulation model and we were able to create ANN models that could predict the simulation model results. The ANN models created were then interpreted and through the interpretation it was possible to rank variables according to their impact on the output results. This makes it possible for decision makers to know how to prioritize and where to place their investments.

Here is the abstract from the article:

This research used a discrete event simulation to create data on a shipment receiving process instead of using historical records on the process. The simulation was used to create records with different inputs and operating conditions and the resulting overall elapsed time for the overall process. The resulting records were used to create a set of predictive artificial neural network models that predicted elapsed time based on the process characteristics. Then, the connection weight approach was used to determine the relative importance of the input variables. The connection weight approach was applied in three different steps:

(1) On all input variables to identify predictive and non-predictive inputs

(2) On all predictive inputs and

(3) After removal of a dominating predictive input.

This produced a clearer picture of the relative importance of input variables on the outcome variable than applying the connection weight approach once.

You are welcome to access the published article at the journal’s website or the full original paper at the ProModel website.

 

Ingalls Develops Automated Unit Lay-Down ‘Advisor’ with Capacity Planning Tool

Image_Ingalls from theSigal MagazineHuntington Ingalls Industries – Ingalls Shipbuilding (Ingalls) identified substantial savings potential in the lay-down placement and assignment process that had been previously utilized for managing asset location throughout the construction process.

Building four different hull forms in the tight shipyard footprint is a challenge. Ingalls Shipbuilding work instructions define the processes and responsibilities for the proper allocation and optimization of real estate (lay-down spaces) for structural units and assemblies under construction, while providing forward visibility for scheduled or potential overloads to capacity.

However, the old capacity planning processes were tedious and overly time-consuming. Resulting real estate allocations were seldom optimal and often required substantial rework to resolve space allocation conflicts, as the construction schedules for each hull form jockey for the same production resources.

The Ingalls team developed an automated process that optimizes unit layout and scheduling, and increases the construction of many units under a covered structure, significantly improving production rates—a plus in the hot southern climate.

“The new tool has taken a process that historically took 10 weeks to complete and can now finish the scheduling activity in less than an hour. Following project completion and full system implementation, we expect to reduce ‘real estate’ allocation processing time by 30% and place 20 more units ‘under cover’ annually, with an estimated cost savings of over $990K per year.”

 (Article Courtesy of “theSignal” and DefenseNews.com)

Click here to read the rest of the Ingalls story

Whirlpool and The University of Michigan Collaborate on a Simulation Project Using ProModel Software

Embarking on a simulation project can seem like a daunting task at times, especially if the project must be completed above and beyond one’s normal responsibilities.  During those times, it is beneficial to consider engaging a partner to help.

Of course ProModel provides professional model building and consulting services, but another alternative is to partner with a University that teaches ProModel, MedModel or Process Simulator.  This type of industry | academia collaboration is a win-win for both organizations.

Please check out this very successful simulation project by Whirlpool on which they partnered with the University of Michigan. The article was published in PlantServices.com.

Click here to see a list of colleges and universities using ProModel software products.  If you would like more information about our academic program, please contact us at education@promodel.com or 801-223-4601.

 

 

From Reality to Model

Adjunct Prof Mark Klee Headshot

Mark Klee; Adjunct Professor – Eastern Kentucky University

I know what you are thinking “From Reality to Model” shouldn’t that be the other way around? As an engineer at Toyota for the past 24 years I often encounter manufacturing processes that have slowly de-optimized. And now, just by walking by the processes on the floor, I can see waste (motion, waiting, over-processing). I know this means that the these processes need some work.

Our typical method of improving these processes would be to employ the traditional Toyota Production System tools. We begin with observation and time study. Then we use video for motion analysis making these processes visual on paper with standardized work combination tables, standardized work charts, and production capacity calculations. Through these simple analysis tools, the waste in the process becomes more obvious and begins to generate ideas for improvement.

This is typically done one process or one zone of processes at at time. It is also usually done with paper, pencil, and stopwatch. The methods have proven time and again to be effective for process improvement and an effective method of developing engineers as well as manufacturing floor members in process improvement.

After the waste is discovered and the improvement ideas generated it is time to try some improvement ideas. The process visualization and capacity calculation documents are then modified to simulate the improvement idea. Then it is time to try the modified process on the production floor. The concept is tested in a controlled environment. After success is documented, the process standards are modified the team is trained to the new standard.

Using ProModel works very well with the Toyota Production System and as a method for developing manufacturing engineers, manufacturing floor members and students in manufacturing focused curriculum. In Eastern Kentucky University’s Applied Engineering and Management class, we follow this progression.

  • We first focus on learning process observation and visualization skill using the standard Toyota Production System tools.
  • Next we learn the processes of implementing controlled change in a mass production environment. We learn and practice these skills on the manufacturing floor to gain real world experience.
  • After learning the basics of observation and improvement, we come back to the classroom where we employ ProModel to fine tune our processes and learn if there are any opportunities for optimization that may have been overlooked.
  • With ProModel we can also test scenarios that may be difficult to test on the actual production floor like moving a piece of equipment, modifying a cycle time, changing a conveyor length or changing a delivery frequency.
  • These trials can be done as quickly as you can change the numbers in the model allowing for many more cycles of trial and error or trial and success in a shorter time.

As a result of the course and ProModel, students have deeper understanding of both the theory and application of process improvement allowing them to be an instant contributor to a manufacturing organization upon their graduation.

In the end, deeply understanding the current reality through observation, documentation, and modification of the current process helps us make a more accurate model. The result of the more accurate model is further optimization. This deepens learning and the improvement cycle continues.

Brief Bio:

Mark Klee, BS Eastern Kentucky University 1990, MS Purdue University 1992
Toyota Motor Manufacturing Kentucky 1994-Present
Eastern Kentucky University Adjunct Faculty 2012-Present

American Food Manufacturer Shows Packaging and Palletizing Improves Production and Plans for Growth with the Use of Simulation

CHALLENGES

An American food manufacturing facility was looking to buy a new palletizer for their packaging/palletizing floor. The manufacturing group needed to perform a capacity analysis of the 13 existing palletizers in the facility which supported 29 production lines. The company was facing challenges keeping up with consumer demand for their popular products. ProModel was brought in to build a pilot model of the packaging and palletizing floor.

OBJECTIVES

The first set of objectives were to analyze and understand the following elements of the current operations:

  1. Case type throughput for an eight-hour shift
  2. Packaging line downtimes
  3. Palletizer utilization

The next set of objectives involved analyzing the impact of different changes to the system:

  1. Cases per pallet
  2. Conveyor length
  3. Adjusting palletizer downtimes

SOLUTION

A ProModel consultant and the company’s personnel worked together to build a pilot model. Packing lines to conveyors to palletizers are represented in the simulation model shown below.

The diagram does not reflect the actual conveyor layouts, but by using data provided by the company, actual conveyor speeds and distances were taken into consideration. The conveyors and palletizers being considered for future expansion were also included in the model.

SS-Palletizer-Improvement_Image_3

More changes to the system can be analyzed since the simulation model is extremely customizable. For example, as additional downtime information is collected, the model can be dialed in to better reflect actual operations. The model allows for other process changes over time too like cycle times, introduction of new cases and new palletizers.

As a result of the success of the pilot model, this company and ProModel will be working together to model another palletizing floor of the facility. The one change that the client requested is that actual conveyor layouts be reflected in this second model to better illustrate how they impact production flow.

VALUE PROVIDED

The company has a model of each palletizing floor. These models can be connected and the organization can test and evaluate changes and expansions to the entire palletizing portion of their facility to guarantee that variations and increases in consumer demand will be met.