Through the Grater

By Helen S. Joyner, Clinton Stevenson

Abstract

In this interrupted case study, students assume the role of a quality assurance intern at a plant that manufactures shredded cheese. As there is no formal sampling plan in place to ensure product quality, students are tasked with developing a feasible plan based on specified safety and practicality factors. In the process, they gain experience in adjusting sampling plan parameters to create operational characteristics (OC) curves with particular shapes, as well as practice calculations for acceptance quality limit and limiting quality. The case was developed for an upper-level undergraduate statistical food quality management course. It would also be appropriate for use in any undergraduate or graduate course that covers principles of statistical quality management and quality management tools, such as operations management courses and statistics courses that cover quality management. It is highly recommended that the case be used only with students who are familiar with the concepts taught in undergraduate statistics.

Download Case

Date Posted

01/31/2019

Overview

Objectives

Design a method of sampling from product lots, given information about lot size and organization.
Construct single acceptance operating characteristics curves for a given lot of product.
Construct double acceptance operating characteristics curves for a given lot of product.
Adjust single acceptance operating characteristics curves to achieve a desired producer's risk, consumer's risk, acceptance quality limit, and/or limiting quality.
Compare and contrast different sampling plans in terms of factors involving quality and safety.
Explain sampling plan principles clearly and concisely to individuals who are not trained in quality management.
Select the appropriate distribution (Poisson or binomial) for calculating OC curves.

Keywords

Statistics; quality control; quality management; food safety; food quality; food science; cheese; OC curve; operational characteristics; sampling plan

Subject Headings

Food Science / Technology

Statistics

EDUCATIONAL LEVEL

Undergraduate upper division, Graduate, Continuing education

FORMAT

PDF, Excel

TOPICAL AREAS

N/A

LANGUAGE

English

TYPE/METHODS

Interrupted

Teaching Notes & Answer Key

Teaching Notes

Case teaching notes are protected and access to them is limited to paid subscribed instructors. To become a paid subscriber, purchase a subscription here.

Teaching notes are intended to help teachers select and adopt a case. They typically include a summary of the case, teaching objectives, information about the intended audience, details about how the case may be taught, and a list of references and resources.

Download Notes

Answer Key

Answer Keys are protected and access to them is limited to paid subscribed instructors. To become a paid subscriber, purchase a subscription here.

Download Answer Key

Materials & Media

Supplemental Materials

Videos

Double Acceptance Sampling Plans
This video explains how to construct an operating characteristic (OC) curve for a double acceptance sampling plan, using chocolate as an example. Running time: 3:39 min. Produced by Clinton Stevenson, NC State University, 2014.
Evaluating Acceptance Sampling Plans
This video explains how to determine the producer's risk and consumer's risk of acceptance sampling plans, as well as how to determine the average outgoing quality (AOQ), average sample number (ASN), and average total inspection. Running time: 4:55 min. Produced by Clinton Stevenson, NC State University, 2014.
Determining Sample Size in Acceptance Sampling
This video explains how to calculate the sample size for different sampling plans with various acceptance numbers, given a particular producer's risk (alpha) and acceptance quality limit (AQL). Running time: 2:47 min. Produced by Clinton Stevenson, NC State University, 2014.
Determining Probability of Acceptance in Sampling
This video explains how and when to use the Poisson probability distribution as an approximation for the binomial probability distribution when constructing operating characteristic curves. Running time: 4:05 min. Produced by Clinton Stevenson, NC State University, 2014.