MEMORANDUM
To: Shuzworld
From: Renado Prince Director of Operations
Re: Operations Recommendations
Date: March 20, 2014

A) Work Flow
Work flow for the assembly line needs to be organized so that it is at its most efficient for production purposes. Application of the proper metrics will help determine the most productive number of work stations for production of our product. Based on the data provided in this scenario, I have determined that the decision analysis tool that deal with layout strategies is the best we can use to reach the correct decisions. It is my recommendation that Shuzworld Shanghai production use employ an assembly and balancing strategy. The layout used by Shuzworld must support its business priorities, quality of work, customer contact and flexibility.
Shuzworld desires to; Make a safer work environment, while maintaining flexibility. It also wishes to improve morale, improve material flows and its utilization of its people, space and equipment. This describes what Production Oriented Layout could do for Shuzworld, and why it Production Oriented layout best suit Shuzworld’s operations.
Shuzworld currently operates on a 40 hour work week and has budgeted production of 6 6 work boots in one hour. The current layout accommodates a good working relationship between personnel and machine utilization.
Based on my findings, I recommend that production be organized into five (5) workstations that produce the Rugged Wear work boot product.

Station Task Time (minutes) Time left (minutes) Ready tasks Assgnd stat work time A
1 A 10 0 B,C 10
2 B 6 4 C C 3 1 D 9
3 D 8 2 E,F 8
4 F 4 6 E E 3 3 G G 3 0 H 10
5 H 9 1 9 Total 4 Maximum 10
Summary Statistics
Maximum cycle time 10 minutes
Time needed (sum of task times) 46 minutes/unit
Min (theoretical) # of stations 5
Actual # of stations 5 Results below based on Act cycle time Time allocated (cycle time * # stations) 50 minutes/cycle
Idle time (allocated-needed) 4 minutes/cycle
Efficiency (needed/allocated) 92%
Balance Delay (1-efficiency) 8%
Based on my computations, a setup of five workstations would get a result of 10 minutes or less per work station. With a five station layout, ten minutes or less per station, the total cycle time would be 46 minutes.

Cycle times per task under my recommendation would be:
TASK TIME
A 10 min
B&C 9
D 8
E ,F, G 10
H 9
It will be necessary to cross train employees due to their workstation performing multiple task at the one station. By cross training our employees, we will be able to later reduce time and keep the process moving at the desired pace due to the employees knowledge of what’s required for completion of the tasks as well as their acquired experience due to the cross training. This model produces the most advantageous arrangement for production and will garner a 92% efficiency rating and an 8% balance delay (1 efficiency rating).
During my analysis, I made the assumption that the specialized equipment needed for production will work well with the materials used for production of the product and that there is a high volume for the equipment being utilized. I also assumed that that a series of workstations would be putting together fabricated parts and that the layout will meet the required output. Lastly I assumed that the procurement of specialized equipment was warranted by a stable demand for the product, and that this strategy would minimize imbalances between personnel and machines and improve workflow.
A1. Justification
The strategic importance of the learning curve is the development of decisions on cost, prices, opportunities and levels of employment. We can achieve this by being able to reproduce the same predictable results during production, but by using less time in reaching that outcome through avoidance of unnecessary actions in the process. Through elimination of unnecessary actions, the production line will be able to find idle time which can be converted and used for production time of the product. The availability of resources and the process of change can affect the learning curve. The proper use of the learning curve can result in maximization of efficiency, time utilization and savings in production of the product.
A1a. Justification Output
In order to determine the most efficient number of workflow stations, processes, performance times and sequence requirements for the task we needed for Shuzworld production (A-H), we entered the task into the assembly line balancing tool. The output of the assembly line balancing tool indicated that five work stations was the optimum number of stations for production. This tool was selected because it aids in achieving higher efficiency while at the same time reducing floor space. By having a properly balanced line, we will see lower production cost and greater throughput.
Results Summary
Cycle time 10
Time needed per cycle (S task times) 46
Min (theoretical) # of stations 5
Actual number of stations 5
Improved cycle time = Maximum station cycle time 10
Time allocated per cycle 50
Idle time per cycle 4
Efficiency 92.00%
Balance delay 8.00%
The workstations for the 5 most efficient productions are listed below. * Workstation 1: Task A * Workstation 2: Tasks B and C (with 1 minute idle time) * Workstation 3: Task D (with 2 minute idle time) * Workstation 4: Tasks E, F, and G * Workstation 5: Task H (with 1 minute idle time)
I utilized the assembly line balancing tool because it allowed me to minimize the number of workstations required for production, while allowing me to maximize efficiency. The assembly line balancing tool allowed me to consider the accomplishment of the needed task by evaluating the most difficult/time consuming task to be placed first, followed by less difficult task that were less time consuming, which flowed into the next task logical. This was achieved through the use of the heuristics algorithms within the tool. The times that were generated were as close to the cycle times as possible and was judged to produce an efficiency rating of 92% for the assembly line.
Based on my findings, the five station assembly line will be the most productive configuration for the production Shuzworld’s new product. Under this configuration there is only four minutes of downtime in the assembly line.
A1ai. Work Flow Analysis Tool
By utilizing the POM for Windows, we come up with a learning curve of 80% referencing the production of Maui Sandals (finding out how many production hours are required for each shipment). Initial production predictions indicated that 1000 working hours would be need for production of the product and that fifty (50) episodes would be needed. These predictions took into consideration; 1) the first four months hours for production, 2) direct labor cost for the company. The episodes are:
5 for month 1
10 for month 2
15 for month 3
20 for month 4
Month one produces five episodes for the company. The first episodes of production will take longer to produce because they are at the front end of (learning curve) production. The preceding batches will require less time as unnecessary steps and experience kick in. The first five batches produced by the company will consume 3737.741 hours of production time, with an estimated $1.08 per hour cost for labor. The first month’s labor cost will be $4036.76. The company should experience production increases from batch 5 to batch 10……The budgeted hours and cost are displayed below:
Time Frame Labor Hours Labor Cost
Month1 3737.741 $4036.76
Month 2 4772.7959 $5154.62
Month 3 5509.3561 $5950.10
Month 4 6101.821 $6589.97
B. Cost Analysis
The learning curve tool is helpful when determining to continue or discontinue producing new products. The learning curve tool also aids in strategic planning. I recommend the use of the learning curve to analyze production of Maui Sandals product line. The idea behind the learning curve is that workers become better at assigned task as that task is repeated. This repetition leads to faster more efficient completion of the task when lends to lower production cost. My cost estimates indicate that a four month run of Maui Sandals will require 20,121.714 hours of labor at a cost of $1.08 per labor hour. The total labor cost will be $21,731.41.
Time Frame Labor Hours Labor Cost
Month1 3737.741 $4036.76
Month 2 4772.7959 $5154.62
Month 3 5509.3561 $5950.10
Month 4 6101.821 $6589.97
The tool used indicates that as more Maui Sandals are produced more efficiently, labor hours required for production will decrease leading to a slow decline in labor cost as production continues. Strategically, the learning curve tool will help reach viable decisions in the areas of employment levels, cost, capacity and pricing. For there to be a learning curve, the Shuzworld must undergo change that causes a cost savings volume increase. The change may stem from available resources and a process change. I selected the learning curve tool because it helps efficiently manage time by causing change that allows more time used for production because less time is needed to produce the product.
B1. Impact
Data gathered can be used to plan for cost, budget forecasting, labor cost and schedules. There is a strategic application for the data I that it could used to assist in evaluating the industry and company’s performance (cost and pricing). Based on the available information the initial cost estimates for production of Maui Sandals was $5400 for the first month (1000 x 5= 5000 x 1.08= $5400). As production continues we should see a decrease in labor hours when compared to the initial production phase. Analysis shows 6101.82 labor hours consumed to produce four times as many sandals than the first batch which required 3737.741 labor hours to produce the first five bathes of the same product. I recommend that Shuzworld continue the production of Maui Sandals. If Maui Sandals production is continued, the company needs to grow its capacity ahead of demand for the product and follow and aggressive pricing policy. Additionally the company should strive to build a shared experience and focus on continued reductions in cost and improvements in production. Shuzworld will place itself in a stronger financial position by cost control earned through the use of the learning curve.
B2. Cost Analysis Output
The POM for Window Learning Curve module was selected because it was able to calculate available information and come up with options for finding time when a coefficient was provided. The coefficient used in this case was 80%. Premise: There will be a doubling in production that will decrease time used to produce each unit, which in turn affects the learning curve. The decrease in production time occurs from the repetition of the task in production and learned experiences in that process that lead to a more effective and efficient method of completion.
Time calculation for 50th unit, T50 = T 1 x (Nb) = 1000 x (50 – 0.322) = ; where
T 1 = 1
Labor time for T 1 = 1,000
Last unit T50 = 50
POM output learning curve coefficient
Table 5.
Learning Curve Coefficient
| |
|Task 2 QB2 Solution |
|Parameter |Value |
|Find learning coefficient given 2 | |
|times | |
|Unit number of base units |1 |
|Labor time for base unit, Y1|1000|
|Unit number of last unit, N |50 |
|Labor time for last unit, YN |284 |
|Learning curve coefficient |.8001 |
Input values for labor time calculation:
Learning curve coefficient = 0.8; Last unit = 50, Base unit labor time = 1,000
Labor Hour Calculation
|QB 2 Step 2 Solution |
|Unit | Production Time |Cumulative Time |
|1 |1000 |1000|
|2 |800 | 1800|
|3 |702.1037 |2502.104 |
|4 |640 |3142.104 |
|5 |595.6373 |3737.741 |
|6 |561.683 |4299.424 |
|7 |534.4896 |4833.914 |
|8 |512 |5345.914 |
|9 |492.9496 |5838.86 ||
|10 |476.5099 |6315.374 |
|11 |462.1111 |6777.485 |
|12 |449.3464 |7226.931 |
|13 |437.9155 |7664.747 |
|14 |427.5916 |8092.338 |
|15 |418.1992 |8510.537 |
|16 |409.6 |8920.137 |
|17 |401.6834 | 9321.82 |
|18 |394.3597 |9716.18 |
|19 |387.555 |10103.73
|20 |381.209 |10484.94 |
|21 |375.2671 |10860.21 |
|22 |369.6889 |11229.9 |
|23 |364.4362 |11594.33
|24 |359.4771 |11953.81 |
|25 |354.7838 |12308.6 |
|26 |350.3324 |12658.93 |
|27 |346.1047 |13005.03 |
|28 |342.0733 |13347.1 |
|29 |338.2307 |13685.33 |
|30 |334.5594 |14019.89 |
|31 |331.0463 |14350.94 |
|32 |327.68 |14678.62 |
|33 |324.45 |1500.07 |
|34 |321.3468 |15324.42 |
|35 |318.3619 |15642.78 |
|36 |315.4878 |15958.26 |
|37 |312.7173 |16270.98 |
|38 |310.044 |16581.03 |
|39 |307.4621 |16888.49 |
|40 |304.4621 |16888.49 _
|41 |302.5517 |17496.01 |
|42 |300.2137 |17796.22 |
|43 |297.9481 |18094.17 |
|44 |295.7511 |18389.92 |
|45 |293.6192 |18683.54 |
|46 |291.549 |18975.09 |
|47 |289.5374 |19264.62 |
|48 |287.5817 |19552.21 |
|49 |285.6791 |19837.88
|50 |283.8271 |20121.71 | Unit Number Time Required
First 1 3737.741
Last 4 6101.81
Results b 0.35353651
Learning curve coefficient 1.27768882
Time for first unit 3737.741

Unit Time Cumulative time
Unit 1 3737.741 3737.741
Unit 2 4772.7959 8513.410879
Unit 3 5509.3561 14025.15423
Unit 4 6101.821 20126.97423
B2a. Cost Analysis Tool
My recommendation is that Shuzworld employ the learning curve tool because it is a valuable tool for negotiating prices, can help managers determine supplier’s cost and can help determine labor hour requirements. The learning curve tool also give mathematical relationships between the time required for production, how many units were produced, how long production took and previous production time. The learning curve allows us to forecast (scientifically) varying production scenarios by using logarithmic and mathematical analysis in conjunction with the learning curve coefficient. Application of the learning curve will assist in making good Continue Production/Discontinue Production decision making calls. All of these positives clearly identify the learning curve tool as a strategic planning asset.
C. Staffing Plan Recommendation
The use of prioritization in scheduling can help address issues such as allocation and timing of operations which the company is currently experiencing difficulties with. This is why I recommend the implementation of the short term scheduling assignment method for Shuzworld production of the Maui Sandals product. Short term scheduling will enable Shuzworld to maximize resources and allow the company to achieve its objectives for production. In order to be successful, the company must minimize work processes, maximize use of the facility and stay focused on the minimization of task completion times. This approach also addresses timing of operations issues. (Heizer, 2010)
C1. Staffing Plan Output
This shows a cost projection ($37) for jobs as they are laid out.
Job assigned Cost
Job 1 Machine A 10
Job 2 Machine B 9
Job 3 Machine D 9
Job 4 Machine C 9 Total 37
I recommend that the company shift operations around to save in production.
C1a. Staffing Plan Analysis Tool
The use of the assignment tool will help avoid overloading and overcrowding the facility. The assignment tool helps to effectively manage facility work flow Input / Output methodology. This in turn allows for a better tracking and monitoring of work flow. If the assignment tool is not used, it could result in inefficiencies and quality problems with the production of the product.
I selected the assignment tool because it was able to effectively analyze the four machines/jobs and come up with the lowest cost for Shuzworld production of the Maui Sandals. This tool provides analysis that gives Shuzworld minimization of cost and time in completing the assignment by each machine. Based on the aforementioned information, I recommend Shuzworld utilize this method for job loading so that completion, idle times and cost are minimized.
D. Outline
When we speak of efficient in the area of scheduling, what we really mean is faster and dependable delivery of the company’s product from its facilities. From this point of view, short-term scheduling could be considered as a process that streamlines transportation of goods and improves efficiency. Through the use of short term scheduling, Shuzworld will have a cost of $7 for movement of the product through the system. (Heizer, 2010)
Job assigned Cost
Job 1 Machine 2 3
Job 2 Machine 3 2
Job 3 Machine 1 2 Total 7
Two short-term scheduling techniques that could work for Shuzworld production are; Work Center Loading, which assigns jobs to work centers. These jobs are assigned so that idle time and completion of task times are kept to a minimum. Division may take two forms which one is capacity oriented and the other assignment of specific jobs to work stations. In short, Input/ Output control and Gantt Chart are used. Gantt chart shows the idle time for different machines, departments or facilities, but they do not take in to account production variances and must be updated on a regular bases.
Another is the use of Job Sequencing which is the arrangement of jobs in the order the need to occur. Johnson’s Rule applies here.
Johnson’s Rule
Applied when there is more than one work center. Under Johnson’s Rule, jobs are assigned to a machine based shortest completion time and minimization of processing and idle times by using four steps.
1. All jobs and job’s times are written down and assigned to a machine.
2. The job with the shortest time is selected.
3. If that job is assigned to the first machine, it’s scheduled first. If that job happens to be assigned to the second machine, it is scheduled last.
4. The job is then removed from the list and steps are repeated until there are no more unscheduled jobs.
Through these steps, you should see a reduction in processing and down time fir a work hub through sequencing.

Scheduling Criteria Minimum customer wait time
Minimum completion time Evaluation determines the average completion time of each job Minimum work in process inventory
Maximum utilization
Evaluation determines utilization percentage of facility Evaluation determines average number of jobs in system. Evaluation is based on determination of average number of late days

References

Heizer, J., & Render, B. (2010). Operations management. New Jersey: Pearson.