Gross & Associates » Case Study http://www.grossassociates.com Consultants in Material Handling Logistics Mon, 12 May 2008 17:08:40 +0000 http://wordpress.org/?v=2.3.2 en Network Modeling helps Consumer Electronics Company with merger http://www.grossassociates.com/2008/02/08/network-modeling-helps-consumer-electronics-company-with-merger/ http://www.grossassociates.com/2008/02/08/network-modeling-helps-consumer-electronics-company-with-merger/#comments Fri, 08 Feb 2008 13:23:41 +0000 Fernando Gonzalez http://www.grossassociates.com/2008/02/08/network-modeling-helps-consumer-electronics-company-with-merger/ Due to a merger between our client and a competitor consumer electronics company, Gross & Associates was tasked with determining the future distribution network for the combined entities. Our client was in the midst of constructing a new warehouse in the Southwest, while the merging company had two distribution centers, one in the Midwest, the other on the East Coast. Both facilities were relatively new and could handle increases in inventory and volume. The new Southwest warehouse was also being built to handle significant expansion, with the possibility of a merger contingent on the construction. Due to the time sensitivity of new product releases to company-owned stores, a majority of orders were sent via UPS or FedEx overnight or 2-day shipments. Each company had negotiated discounts rates with their respective shipping carrier.

Gross & Associates was retained to develop a network model based analysis to determine the least cost distribution network that could service each company’s store sales requirements, including the location of each facility, the size requirements, and the suitability and cost savings in using one or more of the existing warehouse locations.

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]]> http://www.grossassociates.com/2008/02/08/network-modeling-helps-consumer-electronics-company-with-merger/feed/ Simulation helps improve material handling methods for a major building materials manufacturer http://www.grossassociates.com/2008/02/07/simulation-helps-improve-material-handling-methods-for-a-major-building-materials-manufacturer/ http://www.grossassociates.com/2008/02/07/simulation-helps-improve-material-handling-methods-for-a-major-building-materials-manufacturer/#comments Thu, 07 Feb 2008 15:24:53 +0000 Todd Richter http://www.grossassociates.com/2008/02/07/simulation-helps-improve-material-handling-methods-for-a-major-building-materials-manufacturer/ A building materials manufacturer with nationwide manufacturing locations had to replace an aging fork lift truck fleet and upgrade its material handling methods.

The company manufactures materials which are shipped to customers within the service region of each of its sixteen plants. Finished goods are stored both indoors and outdoors. The putaway operation began at the end of the manufacturing line from a palletizing station and finished at an outdoor storage area, nearly ΒΌ of a mile away. Management knew that a better method was needed.

Gross & Associates, the leading material handling consultant in the industry, with over 40 years of experience designing operations for warehousing, distribution, and manufacturing facilities, was asked to develop recommendations to improve the putaway operation and model the new process using computer simulation to help management with the decision process. Management needed to be convinced that changes to the current methods and equipment would improve productivity and reduce staffing requirements.

After an extensive review of the operation, Gross & Associates recommended that finished goods pallets be transported on trains of carts towed by propane counterbalanced fork lift trucks and unloaded by the same trucks at the storage area.

The existing operations were measured and benchmarked against industry standards. The information and data were compiled to model the output of the manufacturing line and putaway process. A computer simulation model was used to test alternatives to determine the equipment and staffing limits of the system at different levels of production.

The results of the simulation model showed that two forklift trucks working at 67% of their maximum capacity could handle the production rate of two simultaneously running production lines.

As a result of the analysis and conclusions drawn from the simulation model, the company implemented the recommendations. They were able to re-use a total of 24 fork lift trucks from its aging fleet significantly reducing capital expenditures. Equally as important, staffing was reduced by 25% as a result of process improvement recommendations. In addition to these cost savings, tighter control over the operation, improved safety and greater throughput capacity were achieved.

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