466 Part Six Case Studies EXHIBIT 1 Sample bag weights. Avg. Weight Range Avg. Weight Range (pounds) Smallest Largest Time (pounds) Smallest Largest Time 48.7 50.7 6:00 A.M. 46.8 41.C 51.2 6:00 A.M. 49.6 49.1 51.2 7:00 50.0 46.2 7:00 50.2 51.7 49.6 51.4 8:0 47.4 44.0 48.7 8:00 50.6 9:00 50 .8 50 .2 51 .8 9:0 47.0 44.2 48.9 49.9 49.2 52.3 10:00 47.2 46.6 50.2 10:00 50 .3 48.6 51.7 11:00 48.6 47.0 50.0 11:00 48.6 46.2 50.4 12:00 midnight 49.8 48.2 50.4 12:00 noon 50.0 1:00 A.M. 49.6 48.4 51.7 1:00 P.M. 49.0 46.4 46.0 50.6 2:00 50.0 49.0 52.2 2:00 49.0 50.0 49.2 50.0 3:00 49 .8 48.2 50 .8 3:00 50 .3 49.2 52.7 4:00 47.2 46.3 50.5 4:00 51 .4 50.0 55 .3 5:00 47.0 44.1 49.7 5: 00 48.4 45.0 49.0 6:0 51.6 49.2 54.7 6:00 51.8 50.0 55.6 7:00 48.8 44.8 49.7 7:00 51.0 8:00 48.0 51 .8 8:00 48.6 53 .2 49.6 50.5 49.4 52.4 9:00 50.0 48.1 52.7 9:00 10:00 49.2 46.1 50.7 10:00 51.0 48.1 55 .2 11:00 49.0 46.3 50 .8 11:00 50.4 49.5 54 .1 48.4 45.4 50.2 12:00 noon 50.0 48.7 50.9 12:00 midnight 1:00 A.M. 47.6 44.3 49.7 1:00 P.M. 48.9 47.6 51.2 2:00 47.4 44 .1 49.6 2:00 49.8 48.4 51.0 3:00 48.2 45.2 49.0 3:00 49.8 48.8 50 .8 4:00 48.0 45.5 49.1 4:00 50.0 49.1 50 .6 5:00 48.4 47.1 49.6 5:00 47.8 45.2 51.2 6:00 48.6 47.4 52.0 6:00 46.4 44.0 49.7 7:00 50.0 49.2 52 .2 7:00 46.4 44.4 50.0 49.0 52.4 8:00 47.2 46.6 48.9 8:00 49.8 50.3 49.4 9:00 48.4 47.2 49.5 9:00 51.7 50.7 10:00 50.2 49.6 51 .8 10:00 49.2 48.1 11:00 50.0 49.0 52.3 11:00 48.4 47.0 50.8 12:00 noon 50.0 48.8 52.4 12:00 midnight 47.2 46.4 49.2 1:00 P.M. 50.1 49.4 53 .6 1:00 A.M. 47.4 46.8 49.0 2:00 49.7 48.6 51.0 2:00 48.8 47.2 51.4 3:00 48.4 47.2 51.7 3:00 49 .6 49.0 50.6 4:00 47.2 45.3 50.9 4:00 51.0 50.5 51.5 5:00 46.8 44.1 49.0 5:00 50.5 50.0 51.9n A2 D3 D4 2 1.880 0.000 3.267 3 1.023 0.000 2.575 4 0.729 0.000 2.282 5 0.577 0.000 2.115 6 0.483 0.000 2.004 7 0.419 0.076 1.924 8 0.373 0.136 1.864 0.337 0.184 1.816 10 0.308 0.223 1.777 12 0.266 0.284 1.716 14 0.235 0.329 1.671 16 0.212 0.364 1.636 18 0.194 0.392 1.608 20 0.180 0.414 1.586 22 0.167 0.434 1.566 24 0.157 0.452 1.548Case Study Bayfield Mud Company excel In November 2011 John Wells, a cus- tomer service representative of Bayfield extremely high cost of oil and natural gas well-drill- Mud Company, was summoned to the Houston, ing operations. Consequently, special use instruc- Texas, warehouse of Wet-Land Drilling, Inc., to in- tions had to accompany the delivery of these spect three boxcars of mud-treating agents that Bay- shipments to the drilling platforms. Moreover, the field Mud Company had shipped to the Houston light-weight shipments had to be isolated in Wet- firm. (Bayfield's corporate offices and its largest Land's warehouse, causing extra handling and poor plant are located in Orange, Texas, which is just west space utilization. Hence, Wells was informed that of the Louisiana-Texas border.) Wet-Land Drilling Wet-Land's Drilling might seek a new supplier of had filed a complaint that the 50-pound bags of mud-treating agents if, in the future, it received treating agents that it had just received from Bay- bags that deviated significantly from 50 pounds. field were short-weight by approximately 5 percent. The quality control department at Bayfield sus- The light-weight bags were initially detected by pected that the light-weight bags may have resulted one of Wet-Land's receiving clerks who noticed that from "growing pains" at the Orange plant. Because the railroad scale tickets indicated that the net of economic conditions, oil and natural gas explora- weights were significantly less on all three of the tion activity had greatly increased. This increased ac- tivity, in turn, created increased demand for products boxcars than those of identical shipments received produced by related industries, including drilling on October 25, 2011. Bayfield's traffic department muds. Consequently, Bayfield had to expand from was called to determine if lighter weight dunnage a one-shift (6:00 A.M to 2:00 P.M) to a two-shift or pallets were used on the shipments. (This might (6:00 A.M to 10:00 P.M) operation in mid-2004 and explain the lighter net weights.) Bayfield indicated, finally to a three-shift operation (24 hours per day) however, that no changes had been made in the in the fall of 2010. loading or palletizing procedures. Hence, Wet-Land The additional night-shift bagging crew was randomly checked 50 of the bags and discovered staffed entirely by new employees. The most experi- that the average net weight was 47.51 pounds. They enced foremen were temporarily assigned to super- noted from past shipments that the bag net weights vise the night-shift employees. Emphasis was placed averaged exactly 50.0 pounds, with an acceptable on increasing the output of bags to meet the ever- standard deviation of 1.2 pounds. Consequently, increasing demand. It was suspected that only occa- they concluded that the sample indicated a signifi- sional reminders were made to double-check the cant short-weight. (The reader may wish to verify bag weight-feeder. (A double-check is performed by the above conclusion.) Bayfield was then contacted, systematically weighing a bag on a scale to deter- and Wells was sent to investigate the complaint. mine if the proper weight is being loaded by the Upon arrival, Wells verified the complaint and issued weight-feeder. If there is a significant deviation from 50 pounds, corrective adjustments are made to the a 5 percent credit to Wet-Land. weight-release mechanism.) Wet-Land's management, however, was not com- To verify this expectation, the quality control staff pletely satisfied with only the issuance of credit for randomly sampled the bag output and prepared the the short shipment. The charts followed by their following chart. Twenty-four bags were sampled mud engineers on the drilling platforms were based and weighed each hour (see Exhibit 1). on 50-pound bags of treating agents. Lighter-weight bags might result in poor chemical control during the drilling operation and might adversely affect Discussion Questions drilling efficiency. (Mud-treating agents are used 1. What is your analysis of the bag-weight problem? to control the pH and other chemical properties of 2. What procedures would you recommend to main- the cone during drilling operation.) This could tain proper quality control? cause severe economic consequences because of theCase Study 5 Bayeld Mud Company Answer the two discussion questions on Page 465. Support question 1 with data analysis. Day shift samples are from 7:00am to 2:00pm. Second shift samples are from 3:00pm to 10:00pm. Third shift samples are from 11:00pm to 6:00am. Note: the time in the rst row of the second Time column on Page 466 should be 6:00pm instead of 6:00am. Construct x-bar and R charts for each of the three shifts. If Bayeld uses these control charts to monitor production, what problems will they encounter when they determine that the process is in control? Explain what a Type I Error would be and a Type II Error would be in the x-bar chart for this process