WMBA 6040 Week 7 Improvement Plan Draft Example

From 8.3 Days Toward Six: The Assembled Improvement Plan for an Optical Lab's Coated Lenses, in Which the Map, Five Measures, the Waste Findings and Three Changes Use One Set of Figures

Student Name

Walden University

WMBA 6040: Improving Business Performance

Instructor Name

Month Day, Year

From 8.3 Days Toward Six: The Assembled Improvement Plan for an Optical Lab's Coated Lenses, in Which the Map, Five Measures, the Waste Findings and Three Changes Use One Set of Figures

The Problem in One Paragraph

Clearwater Optical Laboratory, a wholesale lens maker invented for this course, tells optometry practices to expect coated lenses within five working days. Coated jobs, about 60 percent of volume, actually average 8.3 working days in the building, with a median of 7.8 and a slow tail past twelve. Of that time, under three hours is work; the rest is waiting, most of it for the coating chamber and for the edging queue that coating's batches create. Final inspection rejects 9 percent of jobs, about 58 a day, and every rejected job restarts at surfacing. This plan aims to bring the average coated turnaround to about six business days within two months and to raise first-pass yield from 91 to about 93 percent.

How the Plan Was Built

The plan draws on five earlier pieces of work, each revised here so that all use the same figures. A swimlane map followed one coated progressive job through eleven steps and found four places where work stops. A set of five measures defined how the lab will know whether anything has changed. A Pareto analysis of 1,170 remakes over four weeks showed coating defects as the largest category, and stratification linked those defects to long waits before coating. A waste analysis priced seven categories. And a brief proposed three changes aimed at the constraint.

The Constraint

The map and the remake analysis point to the same place. Because three coating formulations compete for two chamber runs a day, the typical lens sits 2.4 working days waiting for its formulation to come up, and the batches send a wave of several hundred lenses to edging twice a day, adding another 1.4 days. Lenses that wait more than 36 hours before coating fail inspection for coating defects at 7.9 percent, against 2.4 percent for lenses coated within 12 hours. The coating schedule therefore governs both how long jobs take and how many come back.

The Measures

Table 1

The Plan's Five Measures and Their Current Values

Current values are from the four-week baseline; composite figures.

Each measure has a definition tight enough to produce one figure from the lab's scans and an action attached to it. Two analysts will compute the baseline independently before the changes begin; any measure on which they disagree will be redefined first.

The Wastes, Ranked

Waiting is the largest waste by time, about 3.8 days per coated job at coating and edging. Defects are the largest by cost, about $42 per remake and roughly $600,000 a year. Overproduction links them: surfacing turns out roughly a seventh more coated lenses daily than the coating schedule can take, so the queue grows through each week. Inventory, at 46 days of lens blanks against a 20-day target, ties up about $260,000. Motion, transportation and paper reprints are smaller and are left for a second phase.

The Changes

Three changes address the constraint and the largest source of rework.

The first moves coating from two runs a day to four shorter runs, so that every formulation runs at least daily. Capacity is unchanged; the wait for a given formulation falls by about half.

The second caps the queue at coating at 400 trays. When the cap is reached, surfacing switches to uncoated work. Goldratt and Cox (2004) warned that feeding a bottleneck faster than it can work simply piles up trays in front of it; the cap prevents that.

The third adds a shift-start calibration test on the single edger behind most axis errors.

Expected Results

Table 2

Expected Results Eight Weeks After the Changes Begin

Expected values are estimates from the map, the stratification and the queue cap; composite figures.

The trays-in-process estimate follows from the relationship among work in process, throughput and time in the system (Little, 1961): if throughput stays near 650 jobs a day and average time falls toward six days for coated work, the number of trays in the building falls by roughly a quarter.

Questions for Critique

Three questions are offered to reviewers. First, is the defect link strong enough to promise a yield gain, or should the plan promise only turnaround until the four-run schedule has been tested? Second, the plan sets frame holds and incomplete orders aside, though frame holds add about three days to the jobs they affect and incomplete orders about half a day; should either be included now? Third, the plan relies on the coating supervisor to run a new schedule while the production manager enforces the cap; is that division of ownership clear enough? Shah and Ward (2003) found that lean practices worked best as bundles, which argues for including more, while the lab's limited management time argues for less.

Cost of the Changes

The three changes are inexpensive. The four-run coating schedule adds about 1.5 labor hours a day, roughly $9,000 a year at loaded wages, plus a modest increase in coating material per lens. The queue cap requires no spending, only a rule and the production manager's attention. The edger calibration check takes ten minutes a shift, about $2,500 a year. Against these costs, a reduction of about 250 remakes every four weeks would save roughly $130,000 a year at the standard cost of $42 per remake, before counting any business retained from practices that have been receiving late lenses. Even if the defect effect proves smaller than expected, the turnaround gain alone would justify the cost.

References

Goldratt, E. M., & Cox, J. (2004). The goal: A process of ongoing improvement (3rd rev. ed.). North River Press.

Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383-387. https://doi.org/10.1287/opre.9.3.383

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