Statistical Process ControlIntroductionStatistical techniques are playing very important role in the quality control process in every organization; it helps to improve the quality of processes. Statistical process control (SPC) tools are using widely in order to measure and analyze the variation that may present in the processes. Most frequently used for manufacturing processes, the objective of Statistical process Control is to examining and monitoring the quality of product and maintains processes to predetermined targets. Many experts consider the American quality revolution of the 1980s a response to an American quality crisis that had reached major proportions.
This quality revolution led to the overall integration of statistical process control (SPC) and total quality management (TQM) in many U. S. manufacturing sectors. Although manufacturers have used statistical process control (SPC) methods successfully for decades to find causes of poor productivity and to improve product quality, only recently has SPC caught the attention of motor carriers (Mundy, 1986, 25). BackgroundThe purpose of the original study initiated in 1987 was twofold: (1) to demonstrate the application of statistical process control to delivery performance and (2) to explore the potential of SPC in this area of operations.
The research plan included three tasks. The first task was to select the hub-and-spoke terminal networks for analysis and the performance measures of interest. The second task involved data collection and processing from various mainframe databases to create dispatch records. These records contained date-time values for arrivals and departures at selected points along the route from origin to destination. A total of 55,989 complete dispatch records were collected for the period from January 30, 1987, to March 13, 1987. A computer program, written in Statistical Analysis System (SAS) language pieced together dispatch records to create 6,822 completed-shipment records.
Other SAS programs generated random samples and computed the sample statistics needed to build control charts. The third task was to construct control charts, evaluate delivery service quality, and assess the potential of SPC techniques. Analysis Constructing process control charts and assigning causes of unnatural process variation are indispensable steps in any statistical process control program. Although these steps may appear uncomplicated, they present both conceptual and practical problems. The analysis of these problems, as well as the proposed solutions, is presented in two parts.
The first part examines the problems related to charting delivery service. The second investigates issues involved in the search for assignable causes (Richards, 1989, 512). The purpose of this paper is to study the SPC tools applied by the Yellow Freight System, Inc. , on their Less Than Truckload (LTL) delivery service. Charting LTL Delivery ServiceTo construct useful control charts of Less than Truckload (LTL) delivery service, carriers must (1) define and accurately measure delivery service and (2) define a service lane in a way that meets both theoretical and practical requirements.
The kinds of problems that arise when undertaking these efforts are discussed below. Service Measurement Yellow Freight System, Inc. considers the consistency of transit time to be the most critical element of LTL service quality. Transit time is defined as the number of days from pickup until delivery and is measured by subtracting the pickup date from the delivery date.