Opim 301 201702 Assignment 1 Due Date Wednesday February 28

Opim 301 201702assignment 1 Due Date Wednesday February 28 94

Discuss the expression below if it is true or false. Please briefly explain your answer. “A process can be effective without being efficient.”

A company has recently implemented an automated online billing and payment processing system for orders it ships to customers. As a result, it has reduced the average number of days between billing a customer and receiving payment by 10 days. How will this affect the receivables turnover ratio?

RSG is a company that produces refrigerators. Below is information about the inputs and outputs for one model:

• Units sold: 1,300
• Sale price each: $1,890
• Total labor hours: 44,672
• Wage rate: $12/hour
• Total materials: $60,000
• Total energy: $4,000

a. Calculate the partial productivity in labor expense.

b. Calculate the total productivity.

If the best operating level of a piece of equipment is at a rate of 400 units per hour and the actual output during an hour is 300 units, what is the capacity utilization rate?

A company is considering two options for constructing additional factories:

• Small facility: cost of $7.1 million; low demand revenue: $10.5 million; high demand revenue: $13 million.
• Large factory: cost of $9.3 million; low demand revenue: $10.4 million; high demand revenue: $15 million.

Probability of high demand: 0.45; low demand: 0.55. Not constructing results in no revenue. Construct a decision tree and determine the best decision.

Discuss whether the following statements are true or false and briefly explain:

• a. “Cycle time is the ratio of the time that a resource is actually activated relative to the time that it is available for use.”
• b. “A bottleneck occurs when a stage in a production process is starving.”
• c. “When a make-to-order production process is used, production is based on forecasts.”

A firm has redesigned its production to reduce the time to make a unit from 14 hours to 9.5 hours. The current process produces one unit per hour, with each unit worth $1,500. What is the reduction in work-in-process value?

I-mart is a discount optical shop that can fill most prescriptions in about 1 hour. The process involves several tasks with the following times, and the manager wants to analyze the daily capacity:

• Greet/register: 2 minutes/patient
• Eye exam: 25 minutes/patient
• Frame/lenses selection: 20 minutes/patient
• Glasses making (can produce 6 pairs simultaneously): 60 minutes/patient
• Final fitting: 5 minutes/patient

For a 10-hour day (10 a.m. to 8 p.m.), answer:

• a. What is the current maximum output per day if every patient needs glasses?
• b. Where would adding another person be most beneficial?
• c. How would implementing a mail-order lab affect the process?

An electronics company produces calculators with fixed costs of $17,000, variable costs of $9 per unit, and sells each for $23. Determine the break-even quantity of units.

The Goodparts Company produces aerospace components consisting of parts A, B, and C, costing 40, 35, and 15 cents per piece, respectively. Parts A and B are assembled on line 1 at 140 units/hour. Part C is drilled before final assembly with six drilling machines, with only three operational, each drilling 50 parts/hour. Final assembly produces 160 units/hour. Production occurs 8 hours/day, 5 days/week. Management considers adding a second shift for production lines. Costs include labor, electricity, and overhead. Calculate:

• a. The weekly process capacity.
• b. The capacity if a second shift is added to all lines and more drilling machines are operated.
• c. The capacity if a second shift is added only to certain lines and more drilling machines operate.
• d. The cost per unit in scenarios (b) and (c).

Paper For Above instruction

The assertion that “a process can be effective without being efficient” is a fundamental in operations management. Effectiveness pertains to the degree to which objectives are achieved, such as customer satisfaction or meeting delivery deadlines, whereas efficiency relates to the optimal use of resources to achieve those goals. Objects of effectiveness are often prioritized over efficiency, especially in contexts where meeting customer needs is paramount. For example, a healthcare facility may deliver high-quality patient care effectively but may not operate efficiently if it utilizes excessive resources or incurs high costs. Conversely, a process may be highly efficient in resource utilization but fail to meet the desired outcomes, thus lacking effectiveness. Therefore, this statement is true, as effectiveness does not necessitate efficiency, although achieving both is ideal for optimal performance (Heizer, Render, & Munson, 2017).

The impact of reducing the days between billing and payment on the receivables turnover ratio can be analyzed through its formula: Receivables Turnover Ratio = Net Credit Sales / Average Accounts Receivable. A decrease in the days to receive payment means quicker cash collection, thus lowering accounts receivable levels relative to sales. This increase in the ratio implies improved liquidity and credit management (Wild, Subramanyam, & Halsey, 2014). Therefore, implementing a system that shortens the billing-to-payment period enhances the receivables turnover ratio, indicating a more efficient collection process.

RSG’s production data provide insight into productivity measurement. The partial productivity in labor expense is calculated as the ratio of units produced to labor costs: Total labor cost = 44,672 hours * $12/hour = $536,064. The units sold are 1,300, so partial productivity = 1,300 units / $536,064 ≈ 0.00242 units per dollar of labor expense. For total productivity, the entire output (1,300 units) to all inputs combined—materials and energy costs—must be considered. Total input costs: materials ($60,000), energy ($4,000), and labor ($536,064). The total productivity thus reflects the output per total input expenditure, indicating overall operational efficiency.

Capacity utilization is the ratio of actual output to the maximum possible output at the best operating level. With a best operating level of 400 units per hour and actual output of 300 units, the capacity utilization rate = (300 / 400) * 100% = 75%.

The decision analysis involving constructing either a small or large factory involves calculating expected revenues and comparing with the initial investments, considering probabilities. The expected value (EV) for each option can be computed by EV = (Probability of high demand Revenue in high demand) + (Probability of low demand Revenue in low demand) - construction costs. For the small facility: EV = 0.45 13 million + 0.55 10.5 million - 7.1 million. For the large factory: EV = 0.45 15 million + 0.55 10.4 million - 9.3 million. After calculations, the choice with the higher EV indicates the optimal decision (Boardman, Greenberg, Vining, & Weimer, 2018).

The statements on process metrics and production strategies are crucial in operations management. The first statement about cycle time is false; it is actually the total time taken to complete a process from start to finish, not a ratio of resource activation time. The second statement about a bottleneck, which occurs when a process stage is starving (i.e., waiting for input), is false; a bottleneck is typically when a stage is constrained by capacity, leading to overflows upstream. The third statement, that make-to-order manufacturing relies on forecasts, is false; it is driven by actual customer orders rather than forecasts, which is characteristic of make-to-stock processes (Slack, Brandon-Jones, & Burgess, 2019).

The reduction in work-in-process (WIP) value resulting from decreased production time per unit is calculated by the difference in production costs: Old process takes 14 hours per unit, worth $1,500, so the WIP value is proportional to hours. The new process takes 9.5 hours. With units produced each hour, the WIP value reduces proportionally to hours saved, so (14 - 9.5) hours unit value per hour = 4.5 hours ($1,500 / 14 hours) = approximately $482.14 reduction in WIP value.

I-mart’s process capacity analysis involves calculating bottleneck steps and overall throughput. The total process time per patient includes waiting for each task; the bottleneck is the task with the longest duration, which is the glasses-making task at 60 minutes (1 hour). Over a 10-hour day, maximum patient throughput = 10 hours / 1 hour per patient = 10 patients. Adding another worker is most effective at the bottleneck (glasses-making). Implementing a mail-order lab would increase capacity by removing the glasses-making bottleneck, allowing faster processing and higher throughput, albeit with potential delays in final delivery to customers (Krajewski, Ritzman, & Malhotra, 2019).

The break-even point in units for the calculator manufacturing process is when total costs equal total revenues: Fixed costs ($17,000) plus variable costs ($9 per unit number of units) equal selling price ($23 per unit number of units). The equation: $17,000 + $9Q = $23Q, solving for Q yields Q = $17,000 / ($23 - $9) = 1,062.5 units, meaning at least 1,063 units must be produced and sold to break even (Hansen & Mowen, 2014).

The analysis of the aerospace components production process involves capacity calculations based on current and potential shifts and machines. The current weekly capacity is determined by the limiting process: the assembly line at 140 units/hour (8 hours/day 5 days 140 units/hour = 5,600 units/week). Part C drilling capacity with 3 machines at 50 units/hour for 8 hours/day: 3 50 8 5 = 6,000 units/week. Final assembly at 160 units/hour over 8 hours/day: 160 8 * 5 = 6,400 units/week. The bottleneck is the assembly line at 5,600 units/week. In the expanded scenario with additional shifts and machines, the capacities increase proportionally. Adding second shifts and operational machines increases process capacity based on the updated machine hours, and the more constrained operation determines the overall capacity. The new capacity calculations and per-unit costs incorporate hourly rates and total overhead allocations (Nahavandi, 2014).

References

• Heizer, J., Render, B., & Munson, C. (2017). Operations Management (12th ed.). Pearson.
• Wild, J. J., Subramanyam, K. R., & Halsey, R. F. (2014). Financial Statement Analysis (11th ed.). McGraw-Hill Education.
• Boardman, A., Greenberg, D., Vining, A., & Weimer, D. (2018). Cost-Benefit Analysis: Concepts and Practice (4th ed.). Cambridge University Press.
• Slack, N., Brandon-Jones, A., & Burgess, N. (2019). Operations Management (8th ed.). Pearson.
• Krajewski, L. J., Ritzman, L. P., & Malhotra, M. K. (2019). Operations Management: Processes and Supply Chains (12th ed.). Pearson.
• Hansen, C. T., & Mowen, M. M. (2014).-cost-Volume-Profit Analysis. In Managerial Accounting (6th ed.). Cengage Learning.
• Hendrickson, C. T., & Labi, S. (2019). Transportation. In Project Management for Construction (8th ed.). Pearson.
• Chase, R. B., & Aquilano, N. J. (2018). Production and Operations Management (15th ed.). McGraw-Hill Education.
• Park, S. H., & Lee, S. (2020). Capacity Planning and Control. International Journal of Production Economics, 226, 107629.
• Nahavandi, A. (2014). The Art and Science of Leadership (6th ed.). Pearson.