OPS 330 Week 5 Quality and Continuous Improvement Example

Reviewed by Davina Cresswell, MBA · University of Phoenix · Updated

This OPS 330 Week 5 example improves quality in a manufacturing process with data and builds a system that keeps improvement going after the first project ends. University of Phoenix OPS 330 closes with quality improvement and continuous improvement, and OPS/330 wants BS in Business students to combine tools such as Pareto analysis and control charts with a method such as DMAIC or kaizen. The plant is the composite Oklahoma trailer builder whose bottleneck, systems, inventory and planning were addressed in earlier weeks. The paper measures the cost of poor quality from rework and warranty claims, ranks defect types, runs a DMAIC project on weld porosity at the bottleneck, sets a control chart to hold the gain, adds a kaizen routine and daily problem boards and ties quality back to the company's competitive priorities.

CourseOPS 330 Strategic Operations and Logistics (OPS/330)
Week5
Paper typeQuality improvement and continuous improvement plan
Lengthabout 1,040 words, 4 double-spaced pages plus title page and references
FormatAPA 7 student paper
SchoolUniversity of Phoenix
ProgramBS in Business
UpdatedOctober 2026

Free sample paper for OPS 330 Week 5

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Porosity in the Welds and Paint That Peels: Quality Improvement and a Continuous Improvement System for a Trailer Plant

[Student Name]

University of Phoenix

OPS/330: Strategic Operations and Logistics

Week 5 Assignment

[Instructor Name]

[Date]

Red Dirt Trailer Works, its defect data, costs and results are composites written for a model paper.

What this part is doingThe title names the two defects that account for most of the cost.
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Over this course, Red Dirt Trailer Works, the composite livestock and horse trailer builder in Ada, Oklahoma, has found its welding bottleneck, planned an integrated system, set inventory policies and forecast demand. One part of its reputation remains at risk: dealers report more paint problems and weld repairs than they did five years ago. This paper measures the cost of quality problems, runs an improvement project on the largest one and builds a system for continuous improvement.

The Cost of Poor Quality

The team estimated costs from six months of rework logs, scrap tickets and warranty claims, then annualized them: weld rework about $150,000, paint touch-ups and repainting about $110,000, scrap of cut and welded parts about $60,000 and warranty claims from dealers about $90,000. Total internal and external failure cost is about $410,000 a year, roughly 2 percent of sales. Prevention and appraisal, mostly final inspection, cost about $120,000. The balance shows a plant spending far more fixing problems than preventing them.

Where the Problems Are

A Pareto chart of 1,240 recorded defects ranked by count showed weld porosity at 38 percent, paint adhesion failures at 27 percent, wiring faults at 12 percent, misaligned doors at 9 percent and others at 14 percent. Porosity and paint together make up about two-thirds of defects. Porosity matters most because it occurs at welding, the bottleneck: every hour spent grinding out and rewelding a joint is a trailer-hour the whole plant never gets back.

What this part is doingChoosing the defect at the bottleneck connects quality to the throughput analysis from Week 1.
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A DMAIC Project on Weld Porosity

Schroeder et al. (2008) described Six Sigma as a way of organizing improvement that runs alongside the regular hierarchy, with trained project leaders, a fixed sequence of steps and numerical targets, and argued that this structure is what separates it from earlier quality programs. Red Dirt applied the method's five phases with a small team: a welding lead, a quality technician, a maintenance mechanic and the operations manager.

Define: reduce porosity defects in frame and floor welds, which force rework at the bottleneck and cause cracked joints in the field.

Measure: inspectors checked 50 weld joints a day by visual and dye penetrant inspection for four weeks. The average proportion defective was 6 percent.

Analyze: a cause-and-effect session and tests pointed to three causes. Aluminum filler wire stored in an unheated cage absorbed moisture and surface oxide; joints were not always cleaned with a stainless brush and solvent before welding; and on windy days, drafts through open bay doors disturbed the shielding gas. Porosity was about three times higher on windy days and with wire from the cage than with fresh wire.

Improve: wire moved to a heated, sealed cabinet with first-in, first-out rotation; a cleaning station and checklist were added at each bay; and portable weld screens and strip curtains were installed at bay doors. Over the next four weeks, the defect rate fell to about 2 percent.

The most expensive defect in the plant was caused by a cold cage of welding wire and a south wind.

Holding the Gain

A p-chart now tracks the daily proportion of defective joints in a sample of 50. Using the improved average of 0.02 as the center line, the distance from the center to each limit is three standard errors, and the standard error is √(0.02 × 0.98 ÷ 50). That square root is about 0.0198, and three times it is about 0.059. The upper control limit is therefore about 0.079, and the lower limit is zero. A point above the upper limit, or seven days in a row sitting higher than the average, triggers an investigation the same day. The wire cabinet and cleaning checklist become standard work, audited weekly.

What the Welders Thought

The welders were skeptical at first; several believed porosity came from the alloy itself and could not be fixed. Running the comparison of fresh and caged wire in front of them, with dye penetrant results laid side by side, changed minds faster than any presentation. Two welders proposed the weld screens after noticing that the worst joints came from the bay nearest the north door. Their names went on the improvement board, and both joined the paint adhesion team.

Paint Adhesion Next

The second project, on paint adhesion, will follow the same method. Early data suggest inconsistent surface preparation on aluminum, the same root theme of cleanliness that drove porosity.

A Continuous Improvement System

Single projects fade without a system. Bessant et al. (2001) described continuous improvement as a set of behaviors that organizations develop in stages, from occasional problem solving to embedded routines in which improvement is part of everyone's work. Shah and Ward (2003) found that bundles of lean practices, implemented together, were associated with better operational performance. Red Dirt's system has three parts. Daily problem boards at each work area record problems, owners and actions, reviewed in a ten-minute stand-up at the start of each shift. A kaizen event each month brings a cross-functional team together for three days on one process, starting with wiring faults and door alignment. A suggestion process promises a response within five working days and recognizes adopted ideas at the monthly plant meeting.

What this part is doingCiting research on developing improvement behavior explains why the system is built as routines.
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Measures

The plant will track cost of poor quality quarterly, aiming to cut it from about $410,000 to under $200,000 within two years; first-pass yield at final inspection; warranty claims per hundred trailers; weld defect proportion on the p-chart; and the number of suggestions implemented per month.

Quality and Strategy

Quality supports all of Red Dirt's competitive priorities. Durability, one of the reasons customers buy, depends on sound welds and lasting paint. Dependable delivery, the priority dealers stressed, depends on not losing bottleneck hours to rework. Reducing porosity alone returns roughly 12 welding hours a week to production.

Conclusion

Red Dirt spends about $410,000 a year on failures, concentrated in weld porosity and paint adhesion. A DMAIC project traced porosity to wire storage, cleaning and drafts and cut it from 6 to about 2 percent, held by a calculated p-chart and standard work. Daily boards, monthly kaizen and fast responses to suggestions turn that first success into a system for continuous improvement that supports durability and dependable delivery.

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References

Bessant, J., Caffyn, S., & Gallagher, M. (2001). An evolutionary model of continuous improvement behaviour. Technovation, 21(2), 67-77. https://doi.org/10.1016/S0166-4972(00)00023-7

Schroeder, R. G., Linderman, K., Liedtke, C., & Choo, A. S. (2008). Six Sigma: Definition and underlying theory. Journal of Operations Management, 26(4), 536-554. https://doi.org/10.1016/j.jom.2007.06.007

Shah, R., & Ward, P. T. (2003). Lean manufacturing: Context, practice bundles, and performance. Journal of Operations Management, 21(2), 129-149. https://doi.org/10.1016/S0272-6963(02)00108-0

What the OPS 330 Week 5 instructions ask

The last OPS 330 assignment generally asks students to apply quality management and continuous improvement concepts to an organization. Prompts may ask for measuring quality and its costs, ranking and root-cause tools, control charts, improvement methods such as Six Sigma's DMAIC, Lean and kaizen and a plan to sustain improvements. A few prompts also want the earlier weeks' topics pulled together. Use real or realistic data, show the analysis behind each recommendation and support the plan with quality and operations management research cited in APA. Describe how improvement will continue after the first project, not just what the first project fixes.

How this OPS 330 Week 5 example is built

Our model begins with the cost of poor quality: about $410,000 a year in weld rework, paint touch-ups, scrap and warranty claims, roughly 2 percent of sales. A Pareto chart of six months of defects shows weld porosity and paint adhesion making up about two-thirds. A DMAIC project tackles porosity at the welding bottleneck: defining the problem, measuring a 6 percent defect rate in inspected weld joints, analyzing causes such as contaminated filler wire and drafts from open bay doors, improving storage, cleaning and shielding and controlling the result with a p-chart. The defect rate falls to about 2 percent. A continuous improvement system follows, with monthly kaizen events, daily problem boards and a suggestion process with fast responses.

OPS 330 Week 5 grading rubric: where the points go

High grades on this paper go to data-driven improvement with a plan to sustain it. Graders look for quality costs measured or estimated, a ranked view of problems, an improvement method applied step by step with evidence at each stage and a control mechanism such as a control chart with correctly calculated limits. Credit goes to a continuous improvement system that involves employees and to links between quality and the organization's strategy and earlier operations decisions. Research on quality management and continuous improvement supports the plan, particularly studies that explain why improvement efforts fade. Clear charts or tables, accurate calculations and well-cited APA sources earn the remaining points.

OPS 330 Week 5 help: mistakes to avoid

Many quality papers jump to solutions without data. Measure the problem first and show where it is concentrated. Another frequent issue is naming DMAIC phases without showing what happened in each; for every phase, give the evidence or action. Students also present control charts with limits that are guessed rather than calculated. Show the formula and inputs. Some papers end with a single project and no system for continuing improvement, which is the point of the second half of the topic. Describe routines and who runs them. Finally, connect quality back to customers and strategy, for example by showing what a defect costs at the bottleneck compared with elsewhere. A tutor can help you calculate control limits if your formula seems off.

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OPS 330 Week 5 questions, answered

What does OPS 330 Week 5 usually cover?

It usually covers quality and continuous improvement: cost of quality, Pareto and cause-and-effect analysis, control charts, Six Sigma DMAIC, Lean and kaizen and systems for sustaining improvement.

Where can I find a free OPS 330 Week 5 sample paper?

The Week 5 paper above runs a DMAIC project on weld porosity at a trailer plant and builds a continuous improvement system; anyone can read it at no cost.

What is DMAIC?

A five-phase improvement method from Six Sigma: define the problem, measure current performance, analyze causes, improve the process and control it so the gains last.

How are p-chart control limits calculated?

Start with the average proportion defective as the center line. Find the standard error by multiplying that average by one minus the average, dividing by the sample size and taking the square root. The limits sit three standard errors above and below the center, never below zero.

What is kaizen?

A Japanese term for continuous improvement, often applied as short, focused events in which a team studies a process and makes improvements immediately.

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