| Course | OPM-3010 Operations Management |
|---|---|
| Module | Module 5 |
| Paper type | Module 5 written assignment: scheduling, quality management and control |
| Length | About 605 words, 5 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | B.S.B.A. in Operations Management |
| Updated | October 2026 |
Free sample paper for OPM 3010 Module 5
In Control but Not Capable: Loaf Weight Charts and a Specialty Order Schedule
Student Name
B.S.B.A. in Operations Management, Thomas Edison State University
OPM-3010: Operations Management
Mentor Name
Month Day, Year
In Control but Not Capable: Loaf Weight Charts and a Specialty Order Schedule
Control Charts for Loaf Weight
The bakery's 680-gram sandwich loaf must weigh between 670 and 690 grams. Each hour for ten hours, a technician weighed five loaves from the divider.
Shewhart (1931) developed control charts to separate common cause variation, inherent in a process, from special cause variation that signals something has changed. Collier and Evans (2017) give the limits for samples of five as the grand mean plus or minus A2 times the average range for the x-bar chart, with A2 = 0.577, and D4 times the average range for the R chart, with D4 = 2.114 and D3 = 0.
Every sample mean falls between 677.03 and 686.37, and every range falls below 17.12. The chart shows no stretch of seven straight samples sitting together on one side of its middle line. The process is in statistical control: its variation comes from common causes. Sample 8, at 684.6 grams, is the highest mean and coincided with a new flour delivery; it stayed within the limits, but it is worth watching.
| Sample | Mean (g) | Range (g) | |
|---|---|---|---|
| 1 | 680.4 | 15 | |
| 2 | 681.0 | 17 | |
| 3 | 679.8 | 4 | |
| 4 | 681.4 | 4 | |
| 5 | 681.8 | 7 | |
| 6 | 682.8 | 7 | |
| 7 | 681.2 | 6 | |
| 8 | 684.6 | 12 | |
| 9 | 680.8 | 5 | |
| 10 | 683.2 | 4 | |
| Average | 681.70 | 8.10 | |
| Chart | Center line | Lower limit | Upper limit |
| x-bar | 681.70 | 677.03 | 686.37 |
| R | 8.10 | 0 | 17.12 |
Process Capability
Control is not the same as capability. Kane (1986) set out process capability indices that compare the spread of a process with its specification limits. Estimating the process standard deviation as the average range divided by d2 = 2.326 gives 3.48 grams.
A Cp under 1 means the process varies more widely than the specifications allow, and a Cpk of 0.79 means the process, centered 1.7 grams above target, will produce some loaves above 690 grams. The process is stable but not capable.
Two actions follow. Re-centering the divider at 680 grams would raise Cpk to Cp, about 0.96. Reducing variation, for example by servicing the divider's scaling pistons, is needed to reach a Cpk of 1.33, the level many customers expect.
| Index | Calculation | Result |
|---|---|---|
| Cp | (690 minus 670) / (6 x 3.48) | 0.96 |
| Cpk | (690 minus 681.70) / (3 x 3.48) | 0.79 |
Scheduling Specialty Orders
Five specialty orders must pass through mixing and then baking, with one mixer and one oven available.
Johnson (1954) showed that for two stages in sequence, the time to finish all jobs is minimized by choosing the shortest remaining time: if it is in the first stage, schedule the job as early as possible; if in the second, as late as possible. The shortest time is C's 1.0 hour of mixing, so C goes first; next is B's 1.5 hours of baking, so B goes last; then A's 2.0 hours of mixing, early; then E's 2.0 hours of baking, late; D fills the middle. The sequence is C, A, D, E, B.
All five orders finish in 14.0 hours, against 15.5 hours in alphabetical order, saving an hour and a half of oven time on a specialty night.
| Order | Mixing (hours) | Baking (hours) | |
|---|---|---|---|
| A | 2.0 | 3.0 | |
| B | 4.0 | 1.5 | |
| C | 1.0 | 2.5 | |
| D | 3.0 | 3.5 | |
| E | 2.5 | 2.0 | |
| Order | Mixing ends | Baking starts | Baking ends |
| C | 1.0 | 1.0 | 3.5 |
| A | 3.0 | 3.5 | 6.5 |
| D | 6.0 | 6.5 | 10.0 |
| E | 8.5 | 10.0 | 12.0 |
| B | 12.5 | 12.5 | 14.0 |
Conclusion
The loaf weight process is in control but not capable; re-centering and reducing variation are needed. Johnson's rule shortens the specialty schedule by 1.5 hours. Both tools turn data into specific operating decisions.
References
Collier, D. A., & Evans, J. R. (2017). OM (6th ed.). Cengage Learning.
Johnson, S. M. (1954). Optimal two- and three-stage production schedules with setup times included. Naval Research Logistics Quarterly, 1(1), 61-68. https://doi.org/10.1002/nav.3800010110
Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41-52. https://doi.org/10.1080/00224065.1986.11978984
Shewhart, W. A. (1931). Economic control of quality of manufactured product. Van Nostrand.
OPM 3010 Module 5 instructions, in plain terms
The fifth written assignment covers scheduling, quality management and control. Expect problems that ask you to build control charts from sample data, judge whether a process is in control, compute capability indices and sequence jobs with rules such as Johnson's rule. Show each calculation, including the constants used, and interpret the results. Be careful to distinguish a process that is in control from one that is capable, since the two answer different questions and lead to different actions. State your specification limits clearly and compute capability only after confirming the process is in control. For scheduling problems, show the timeline as well as the sequence. Name the constants table you used for your sample size, and keep every intermediate value visible in the work.
How this OPM 3010 Module 5 example is built
The paper tabulates ten samples of loaf weight, computes x-bar and R chart limits with their constants and judges the process in control. A section computes Cp and Cpk and explains why a stable process is not capable, with two actions. A scheduling section applies Johnson's rule step by step, tabulates the resulting timeline and compares the makespan with an alphabetical order. The conclusion ties both tools to operating decisions. Two actions follow the capability result, re-centering the divider and reducing variation, with the Cpk each would reach, so the analysis ends in decisions rather than only numbers. The two tables of limits and indices make each result easy to verify.
Reading the OPM 3010 Module 5 grading rubric
Mentors grade this assignment on correct control limits and capability indices, correct application of scheduling rules, accurate interpretation and clear presentation. Papers that distinguish statistical control from capability show command of quality concepts. Explaining each step of Johnson's rule, rather than giving only the sequence, demonstrates understanding. Recommendations that follow from the numbers, such as re-centering the process, show how quality tools guide action. Recommending specific actions from the capability result, with their effect on Cpk, shows how quality tools guide improvement. Comparing the schedule's makespan with a simple alternative shows the value of the rule. Showing every constant prevents errors.
OPM 3010 Module 5 help from the desk
Students lose points by using the wrong control chart constants, by declaring a process capable because it is in control, by miscomputing Cpk with the target instead of the mean or by giving a sequence without the timeline. Others forget the R chart. Use the constants for your sample size. Check both charts. Compute Cpk from the process mean. Show the schedule's start and end times. Compare your schedule with a simple order to show what the rule gains, and recommend actions from the capability numbers. Watch for runs and trends as well as points outside the limits. A free first sample on your own OPM-3010 quality and scheduling assignment is available on request.
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OPM 3010 Module 5 questions, answered
Where can I find a free OPM 3010 Module 5 sample paper?
Loaf weight control charts, capability indices and a Johnson's rule schedule are worked in the assignment above.
What is the difference between a process in control and a capable process?
A process in control has only common cause variation; a capable process also stays within its specification limits.
What does Cpk measure?
How well a process fits within its specification limits, accounting for how far its mean is from the center.
What is Johnson's rule?
A way to order jobs through two stages in sequence so that the whole batch finishes as early as possible.
What is A2 for samples of five?
0.577, used to set x-bar chart limits from the average range.