Case Studies

Children's Hospital of Pittsburgh of UPMC

2010-11-08T20:05:52Z

The Children’s Hospital of Pittsburgh of UPMC (CHP) had a unique and once-in-a-career problem; how to move 152 children the two and a half miles to its new state-of-the-art facility in a single day, without sacrificing patient safety and without breaking the budget. This was not just a simple matter of shuttling ambulances back and forth. While the problem is simple to describe, there were deceptively complex logistical challenges to address, including the coordination of over 250 staff members, 35 ambulances and scores of specialized, shared pieces of medical equipment. Even elevators had to be considered in the final analysis.

Pharmaceutical Order Processing

2009-10-06T22:35:08Z

Caremark PCS (Formerly Advanced PCS)

The pharmacy benefits group for Caremark looked to simulation to help improve customer service and reduce turnaround time on prescription orders.

Orders arrive to the central processing location in Scottsdale, AZ via telephone, fax, internet, and mail. Each order can then proceed through one of hundreds of possible paths depending on the type of order, the source, if it is a refill or new prescription, and other random factors. Each path will contain anywhere from 4 to15 steps. At each step the order must be processed, and delays may occur.

The sheer volume and complexity of the orders made capacity planning and staffing very difficult. Simulation has helped reduce order turnaround time, improve staff utilization, and reduce costs.

Blending and Packaging Challenges

2009-10-06T21:37:42Z

Unilever (Wish-bone and Lawry's)

Over the course of a long partnership with Unilever's in-house industrial engineers, NovaSim has developed multiple discrete event simulation models to help optimize production performance.

Project Objectives

Determine whether the ingredient preparation system could keep up with increased production, while considering the handling of Kosher ingredients
Create efficient production schedules to meet demand while minimizing losses due to changeovers and equipment availability contraints
Manage dedicated equipment while simultaneously meeting all product demands
Coordinate the batch production and the complex system of ingredient scales with fork lift delivery, pumps, mixers, and packaging lines

Creamy or Crunchy?

2009-10-06T19:30:53Z

Unilever (Skippy Peanut Butter)

The Skippy family of peanut butter includes six different products that are packaged in more than 50 different products for sale around the world. NovaSim worked with Unilever's industrial engineering team to develop a SIMUL8 discrete event simulaiton model that was used to optimize overall production performance for the Skippy brand.

Batch Production

2009-10-06T19:16:52Z

Unilever (Best Foods Mayonnaise)

We have all seen recipes for mayonnaise. The ingredients are very simple: eggs, vegetable oil, maybe some lemon juice, vinegar, salt and pepper. If you set your mind to it, it would be a simple matter to make up a batch in your kitchen. But what if you needed to make more than 1 million pounds per day? NovaSim developed a discrete event simulation model in SIMUL8 to help Best Foods do just that.

Small Project, Big Results

2009-10-06T18:02:06Z

Dynacraft

As consultants we often are faced with large complex projects that span weeks or months. However, simulation also has great benefit on smaller projects. Although this simulation was started and completed within a single day it still has proven to privide significant value to Dynacraft, a subidiary of Paccar Inc.

Setup Time Reduction

2009-10-06T17:41:48Z

Flexfab

In an effort to reduce setup times on key extrusion equipment and balance thier product mix of high volume products and low volume specialty products, Flexfab of Hasting, Michigan looked to SIMUL8 and NovaSim for a solution.

Surgical Scheduling

2009-10-06T16:19:34Z

Hunter New England Area Health Service

Hunter New England Area Health Service is a large governmental health services organization in New South Wales, Australia. Serving approximately 850,000 people, the HNEAHS includes 3 teriary hospitals, 4 rural referral hospitals, 12 district hospitals and 10 community hospitals. NovaSim, working together with PricewaterhouseCoopers Australia, developed a comprehensive simulation model to help manage surgical block management and overall waitlist management for two of the largest facilities in the region. Used to solve a variety of what-if questions when it was first developed, the model remains in consistent use several years later as an ongoing wait list management tool.

Simulating the Johns Hopkins Comprehensive Transplant Center

2009-10-02T00:15:06Z

Johns Hopkins Medical Institute

The number of chronic disease cases is growing at phenomenal rates as our general population ages. End-stage diseases of all the major organs: heart, lung, liver, kidney and pancreas ultimately rely on transplantation as the only means remaining to return a patient to reasonable health.

Because of this growth in demand, the line of patients waiting to receive organ transplants is seemingly endless. Aside from the fact that there are not enough organs being donated to meet this need, the transplant community's next biggest problem is having sufficient resources to meet the increasing demand.

Reducing Cycle Times: Evaluating the American Red Cross' Blood Donor Testing Process

2009-09-30T19:26:03Z

American Red Cross

In the United States, someone needs blood approximately every two seconds. With the American Red Cross providing 50% of this supply, this translates to 6.9 million samples being tested each year. In 1991, the American Red Cross consolidated its network of 53 original Red Cross testing laboratories into nine state-of-the-art facilities. Implementation of standardized operating procedures, training and equipment at the nine National Testing Laboratories (NTLs) improved quality control, facilitated the adoption of new technology, and maximized sample flow and flexibility. Currently, ninety-five percent of all blood is tested within 15 hours from the time the blood samples are received by the NTL; 99 percent of all blood is tested within 24-hours. In an effort to both improve on this high service standard and lower costs, the National Testing and Reference Laboratory Headquarters looked to simulation as a potential tool.