BAYONNE PACKAGING, INC. CASE 1 OPERATIONS MANAGEMENT teached by Manuel Baganha and Virginia Ulfig

GROUP 18 DAVID STIEHL 10217 GONÇALO CORREIA 10613 RUI SOROMENHO 10308 TIAGO SILVA 11006

This case is based only on data available on “Bayonne Packaging, Inc.” by Roy D. Shapiro and Paul E. Morrison

Case 1

BAYONNE PACKAGING INC.
Bayonne is a “specialty packaging” paper converter that produces customized, complex design packaging used by industrial companies in promotional materials, software, luxury beverages, gift food and candy. The company is located in New Jersey, USA and is worth 43 million dollars. In spite the company’s sales growth in the last few
In order to optimize this situation optimal conditions can be computed to find which machine should be used, depending on the size of the order. The quantity at which the machines spend equal time producing the same number of pieces is when the number of pieces produced is 11.023 (see Exhibit 4). Thus orders larger than 11.023 pieces should be allocated to the Royal/Queen. In opposition orders smaller than 11.023 pieces should be send to the Staude. The optimal trade-off between time usage and order size was supposed to be at 60.000 units, according to Gomes, which is very far from the 11.023 and can explain the low capacity utilization of both Staude and Royal/Queen machines. Another concern that is affecting the efficiency and leads to several order conflicts is the parceling of the orders. When the order is running late, a partial quantity is shipped in order to satisfy part of the customer’s needs and maintain service level, while the remaining quantity is delivered to the client when the order is completed. These broken runs while accelerating the most urgent orders are delaying the rest of the production because each broken run causes the need of an extra setup, which takes 40 or 180 minutes (depending on the machine whose run was broken). For instance, the Royal/Queen capacity was reduced from 13.781.614 to 12.192.955 pieces due to partialed orders (see Exhibit 5). Quality and delivery problems caused an increase in costs.