ProModel AutoCAD App for Warehouses and Distribution Centers

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Steve Courtney, ProModel Sr. Consultant

I have several years of experience in supply chain and logistics modeling helping clients who have large warehouses and distribution centers.  These models are often very large (thousands or tens of thousands of locations), which can be very time consuming to model.  I’ve found the old adage to be very true: “Necessity is the Mother of Invention”, so I developed a ProModel App that is used from within AutoCAD which enables us to quickly build the graphical portions of the model using OLE automation.  This capability is also very useful when experimenting with several different layouts.

The types of Warehouse / DC modeling questions that can be answered include:

  • Slotting questions – where should my SKUs go?
  • Racking questions – which type of racking is best (flow rack, bin shelving, single pallet deep, double pallet deep, drive-in racking, etc.)?
  • How high should our racking go 5 levels, 7 levels, etc?
  • Which material handling devices are best – narrow aisle, forklifts, single/double/triple pallet jack, reach trucks, side loaders, clamp trucks, electric/propane/natural gas, etc.?
  • Staffing questions – how many of each type and when?

I recently gave a webinar on this topic which you can view here

The requirements for using the app include:

  • Current AutoCAD drawing
  • AutoCAD not AutoCAD Light
  • Know where each location is physically on the drawing
  • Location levels 2-X should be mapped to the level 1 location
  • Build indexed location file in the order you plan to add to the drawing
  • Know which material handling device accesses each location

If you would like to discuss this further, or have other ideas that can help us all improve warehouse and distribution center modeling, please comment below.  Thanks and Happy Modeling!

Thanks, Steve Courtney

 

Oilfield Equipment Manufacturer Optimizes New Facility Design

CHALLENGES

A leader in the design, manufacture, and supply of oilfield equipment had recently purchased land to build a world class manufacturing facility.  The new location would be designed to capture future growth but needed to be sized correctly; not a wasteful over-construction yet not too small at the same time.

The senior executive team thought simulation modeling would allow them to analyze their manufacturing processes, identify bottlenecks, capture productivity improvements, and properly size the new facility.  After a lengthy vendor sourcing exercise, ProModel Corporation was selected as the best provider to answer this modeling challenge.

OBJECTIVES

  • Model the existing manufacturing processes
  • Identify current process constraints using various customer demand scenarios
  • Simulate maximum throughput potential with the current processes and equipment layout
  • Using LEAN process improvement skills, simulate a more productive manufacturing process and scale that upward to capture growth
  • Simulate the new manufacturing facility and validate the desired growth rates. Upon completion of this step, the layout would be given to the architects for structural design.

VALUE PROVIDED

  • Immediate identification of a critical bottleneck that once resolved, increased cell throughput by 53% and overall production by 19%
  • Throughput has grown 45% since the launch of the initiative due to a much better understanding of their manufacturing methods and related constraints
  • Manufacturing standards used by the production planning team were far from accurate thus creating a workflow imbalance
  • Equipment previously slated for purchase was determined to add no throughput benefit thus saving several hundred thousand in capital expenditures
  • Numerous future state layouts were modeled thus allowing the team to ultimately select the most productive equipment arrangements
  • The simulation model became a powerful sales tool with customers; understanding the flow in the facility and how it could absorb their incremental orders
  • Even during a severe industry downturn, the company continued to capture market share due to improved manufacturing methods.

SOLUTION

A ProModel senior consultant worked with the engineering staff to build dynamic models of their current production facility and planned future construction.

First, a dynamic flexible model of the existing facility was created and validated.  That model was used to define the true capacity of the existing facility, analyze current constraints, evaluate capital improvement options, and test new LEAN concepts that were under consideration for the current and future facility.

A major challenge to creating the model was accommodating the tremendous variety of products manufactured.  A user friendly interface for running the model was developed to provide the ability to run any variation of mix/demand against several operational configurations.

The key learnings from the existing facility model were then applied to the new facility design.  Alternate facility layouts and new material handling concepts were evaluated to ensure the plant of the future would meet all capacity targets.

3D Animation of a Portion of the Plant

3D Animation of a Portion of the Plant

 

Brazilian Academic Simulation Awards Given in Honor of Rob Bateman

ProModel friends and associates, last October 12 we lost a dear friend, Rob Bateman and it is very hard to believe that a year has already passed.  Coincidentally, just a few days before the loss of our colleague, on October 6, 2015, the first ever ‘Rob Bateman’ award was delivered in the city of Joao Pessoa (north east coast of Brazil).  Here is the web site of the event:  http://www.abepro.org.br/enegep/2016/index.asp.  The Simula Brazil is a national award for simulation systems, organized and hosted by the portal “www.simulacao.net” which is sponsored by the Belge Consulting (www.belge.com.br). The award has institutional support of ABEPRO (www.abepro.org.br) and SOBRAPO (www.sobrapo.org.br) and is linked to the National Production Engineering Meeting (ENEGEP).

This award aims to encourage young students to use more simulation technology to develop projects and analyze real or fictitious situations through the use of the ProModel modeling and simulation technology (ProModel® or MedModel®) as well as assisting teachers with simulation education. The hope is that this practice will allow for better industrial engineering courses using ProModel and more simulation use in local companies, as well.  This year the award was given to the following recipients:

originalityaward

Marcelo Fugihara of Belge presenting the award for originality to Jacyszyn Bachega of Universidade Federa de Goias

 

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Marcelo Fugihara of Belge presenting the award for complexity to Thiago Fernando Rosa Tedoro and Professor Jose Lazaro Ferraz of Universidade FACENS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

all-students

Here is a photo of all of the students in attendance at the event, called Enegep –  Encontro Nacional de Engenharia de Produção

We hope that this award in some small way pays tribute to our friend Rob Bateman.

Your friend in Simulation,

Alain de Norman & Belge team.

Teaching Supply Chain Management with ProModel

profshannonPatrick W. Shannon, Ph.D., is a professor of operations and supply chain management at Boise State University. He taught graduate and undergraduate courses in business statistics, quality management, lean manufacturing and other areas of operations and supply chain management. Professor Shannon developed a curriculum for his supply chain class, using ProModel Simulation which he used for over 10 years.

To provide you some insight into how you can use ProModel in the classroom, Professor Shannon was kind enough to allow us to share the materials he used.

Attached are PDFs of his course materials.

  1. Tri-Star Manufacturing: A Case Study in Lean Implementation
  2. The Tri-Star Simulation Model
  3. Project Requirements and Rules
  4. ProModel Instructions

Dr. Shannon served as dean of the College of Business and Economics from 2008-2014 and has lectured and consulted on statistics, lean manufacturing and quality management, project management, statistical modeling, and demand forecasting for over thirty years. He has co-authored 11 university level textbooks, and he has published numerous articles in such journals as Decision Sciences Journal of Innovative Education, Business Horizons, Transportation Research Record, Interfaces, Journal of Simulation, Journal of Production and Inventory Control, Quality Progress, and Journal of Marketing Research, Quality Management Journal, and The International Journal of Quality and Reliability Management.

He completed his BS and MS at the University of Montana and his Ph.D. in Statistics and Quantitative Methods at the University of Oregon. In 2015 he presented at the National Kidney Registry (NKR) Symposium in New York City. The presentation, authored by Shannon and Phil Fry, professor of operations management, is titled “Kidney Life Years” and describes the research Fry and Shannon have conducted with the NKR. The purpose of the research is to develop a statistical model to identify the donor characteristics that impact the length of time live donor kidney transplant will last. modehttp://journals.lww.com/transplantationdirect/toc/2016/07000l

Click here to view his LinkedIn Profile.

If you are a professor interested in learning more about ProModel’s Academic offerings, please email cbunker@promodel.com for more information.  You may also check out the following: www.promodel.com/industries/academic

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One Way Automotive Manufacturers Can Meet the Challenges of a Rapidly Changing Market

The automotive industry is likely to change more in the next 10 years than it has in the previous 50. It seems like in so many industries today including technology, entertainment, and consumer products, change at a very rapid pace.  The auto industry is by far no exception.  There are many new entrants into car making, add to that self-driving vehicles, electric cars, and car sharing just to name a few.  All these factors are providing increased competition.  Not to mention the rapidly fluctuating price of gasoline.  With instability in the Middle-East and increased oil production in the US and other parts of the world, who knows how that may change in the next 6 months.  There is no doubt that reacting quickly and strategically to these rapid demand shifts will be an absolute priority for auto leaders in 2016.

Simulation is a tool that can help automakers accommodate these rapid changes and develop scenarios for planning for the uncertainties that may occur.

Consider that a US plant reduced its work force by 20% in 2010 during the recession.  Not only that, but floor space has been re-arranged to accommodate those reductions.  Now in this post-recession period the demand for vehicles from this plant is increasing rapidly.  How do you meet that demand with the existing workforce? Can you build the number of vehicles necessary without moving lines or cells around again and hiring more workers?  If you do hire, which positions, how many, and on what shifts do you need more FTEs?  Simulation can help you make these decisions more confidently.  Here are some ways in which it has already been done.

The Rim Assembly Model

A large automotive component manufacturer experienced difficulties reaching a desired line speed.  The operation involved mating a set of tires with rims for multiple manufacturers.  The line was consistently under producing and management wanted the problem solved now!  Given the interactions between the various parts of the line, it was difficult to assess which component was the actual bottleneck. Only a limited number of things could be changed, so the objective was to find what modification to the line was possible to achieve improved speed in a short period of time with as little capital investment as possible.  The following modifications were tested:

  • Sequence the tires to the lean cells. The baseline was for tires one and two to go to lean cell one and tires three and four to go to lean cell two.
  • Shorten the load time between rims by staffing and laying out load position differently
  • Use only one lean cell
  • Eliminate the use of “switch-outs” where a failed mating between rim and tire at the lean cell required that the lean cell be stopped
  • Adjust the tire feed spur lengths

The largest gain in line rate required three changes: the time between rim arrivals was reduced from 23 seconds to 16 seconds, the elimination of switch-outs and the lengthening of tire feed spur lengths.

These modifications allowed the client to get to the desired line rate and the model was developed and results were submitted within 5 days. View the video for a quick sample of the model.

Check out one of our success stories about another auto manufacturer: Tofus-FIAT Realizes 48% Reduction in WIP with ProModel Simulation. This solution story is available among many from our online library. Many solution and model videos are also available on our YouTube Channel. If you would like to learn more about ProModel solutions contact us.

Other References:
http://www.weforum.org/agenda/2016/01/the-next-revolution-in-the-car-industry
http://www.mckinsey.com/industries/automotive-and-assembly/our-insights/a-road-map-to-the-future-for-the-auto-industry

Teaching Process Management Using ProModel

ProModel Guest Blogger:  Scott Metlen, Ph.D. – Business Department Head and Associate Professor at University of Idaho

Scott Metlen, Ph.D.

Scott Metlen, Ph.D.

Understanding process management, the design, implementation, management and control, and continuous improvement of the enterprise wide set of an organizations processes is the key to well deployed strategies. It was not until Tim Cook made Apple’s total set of processes world class including all supply chain linked processes (Brownlee, 2012) that Apple hit its amazing climb to become the world’s highest valued company; even though the company had cutting edge products before his arrival. Gaining effective understanding of process management is not easy due to the strategic variability inherent in the portfolio of products that companies sell, and in markets they service. This strategic variability (Rajan, 2011) in turn drives variability in many processes that an organization uses to operate. For instance, different markets require different marketing plans supported by different processes.  Order processes often vary by product and target market. Employee skill sets differ by product requiring different hiring and training processes. Different products, whether it be services or goods that have a slight variation require, at the very least, an adjustment to the production process. Adding to, and often caused by the variability just mentioned, are multiple process steps, each with different duration times and human resource skills.  Depending on what product is currently being produced, process steps, process step order and duration time, interdependency between the process steps, and business rules all vary. Where a product is in its life cycle will drive the experience curve, again creating variation across products. In addition, the numerous interfaces with other processes all vary depending on the product being produced. All of these sources of variability can make process management hard to do, teach, and learn. One tool that helps with process management in the face of variance is discrete event simulation and one of the best software suites to use is ProModel. ProModel is a flexible program with excellent product support from the company.

Effective process management is a multi-step process. The first step of process management is to determine the process flow while at the same time determining the value and non-value added process steps. Included in the process flow diagram for each step are the duration times by product and resources needed at each step, and product routes. Also needed at this time are business rules governing the process such as working hours, safety envelopes, quality control, queueing rules, and many others. Capturing this complex interrelated system begins by visiting the process and talking with the process owner and operators. Drawing the diagram and listing other information is a good second step, but actually building and operating the process is when a person truly understands the process and its complexities.  Of course many of the processes we want to improve are already built and are in use. In most cases, students will not be able to do either of these. However, building a verified and validated simulation model is a good proxy for doing the real thing, as the model will never validate against the actual process output unless all of the complexity is included or represented in the model. In the ‘Systems and Simulation’ course at the University of Idaho students first learn fundamentals of process management including lean terms and tools. Then they are given the opportunity to visit a company in the third week of class as a member of a team to conduct a process improvement project. In this visit students meet the process owner and operators. If the process is a production process, they walk the floor and discuss the process and the delta between expected and actual output. If the process is an information flow process, such as much of an order process, the students discuss the process and, again, the delta between expected and realized output. Over the next six weeks students take the preliminary data and begin to build a simulation model of the current state of the process. During this time period students discover that they do not have all the data and information they need to replicate the actual process. In many cases they do not have the data and/or information because the company does not have that information or how the model is operated is not the same as designed. Students then have to contact the process owner and operators throughout the six weeks to determine the actual business rules used and/or make informed assumptions to complete their model.

Once the model has been validated and the students have a deep understanding of the process, students start modeling process changes that will eliminate waste in the system, increase output, and decrease cost. Examples of methods used to improve the process include changing business rules, adding strategically placed buffers and resources, and reallocating resources. To determine the most effective way to improve the process, a cost benefit analysis in the form of an NPV analysis is completed. The students use the distribution of outputs from the original model to generate appropriate output and then compare that output to output pulled from the distributions of each improvement scenario. This comparison is then used to determine a 95% confidence interval for the NPV and the probability of the NPV being zero or less. Finally, several weeks before the semester is finished, students travel to the company to present their findings and recommendations.

Student learning on these projects is multifaceted. Learning how to use ProModel is the level that the students are most aware of during the semester, as it takes much of their time. However, by the end of the semester they talk about improving their ability to manage processes, work in teams, deal with ambiguity, manage multiple projects, present to high level managers, and maintain steady communication with project owners.

Utilizing external projects and discrete event simulation to teach process management has been used in the College of Business and Economics at the University of Idaho for the past six years. As a result, the Production and Operation area has grown from 40 to 150 students and from five to 20 projects per semester. More importantly, students who complete this course are being sought out and hired by firms based on the transformational learning and skill sets students acquired through the program.

References:

Rajan Suri. Beyond Lean: It’s About Time. 2011 Technical Report, Center for Quick Response Manufacturing, University of Wisconsin-Madison.

Brownlee, John. Apples’s Secret Weapon 06/13/2012. http://www.cnn.com/2012/06/12/opinion/brownlee-apple-secret/index.html?hpt=hp_t2. 12/301/2014.

Scott Metlen Bio:

http://www.uidaho.edu/cbe/business/scottmetlen

 

Flanagan Industries Brings New Facility Online Thanks To ProModel Solution

Flanagan Industries is a major contract manufacturer of aerospace hardware specializing in highly engineered and high value machined components and assemblies.  Over the years their manufacturing operations had been growing steadily to the point where they absolutely needed additional capacity . The original space was not conducive to a manufacturing environment and had become an impediment to taking on more business and staying competitive in the global economy.  So Flanagan decided to expand by opening a new facility that could house bigger and better machinery, however they needed to ensure that the move to the new location would not disrupt their current operations and customer orders.

In the video below, see how Flanagan used a ProModel Simulation Solution to successfully bring their new facility online: