Stanford Rosenberg Computing Wants To Establish An Assembly

911 Stanford Rosenberg Computing Wants To Establish Anassembly Line F

Stanford Rosenberg Computing aims to establish an assembly line for manufacturing the new Personal Digital Assistant (PDA). The process involves several tasks, each with specific durations and immediate predecessor tasks. The tasks are as follows:

  • Task A: 12 seconds, no predecessors
  • Task B: 15 seconds, predecessor: A
  • Task C: 8 seconds, predecessor: A
  • Task D: 5 seconds, predecessors: B and C
  • Task E: 20 seconds, predecessor: D

The goal is to produce 180 PDAs per hour. The questions to consider are:

  1. What is the cycle time?
  2. What is the theoretical minimum number of workstations Rosenberg can achieve?
  3. Can this minimum be practically achieved when assigning workstations?

Sample Paper For Above instruction

The rapid advancement of technology and the increasing demand for portable digital devices have led manufacturing companies like Stanford Rosenberg Computing to optimize their assembly processes considerably. Establishing an efficient assembly line to meet specific production targets requires careful analysis of task durations, precedence relations, and the overall workflow. This paper explores the process design for producing the Personal Digital Assistant (PDA) at a rate of 180 units per hour, focusing on calculating the cycle time, the theoretical minimum number of workstations, and the practical aspects of work assignment.

Introduction

In modern manufacturing, efficiency and productivity are vital to remain competitive. Process design involves analyzing the tasks involved in production, determining their precedence, and structuring assembly lines accordingly. For Stanford Rosenberg Computing, producing 180 PDAs per hour presents a specific challenge that requires a systematic approach to line balancing. Understanding the fundamental concepts like cycle time, theoretical minimum workstations, and practical constraints provides the foundation for designing an optimized assembly line.

Cycle Time Calculation

The cycle time is the maximum allowable time per unit to meet the production goal. It is calculated by dividing the available production time by the demand. With a goal of 180 PDAs per hour, the total available time per hour is 3600 seconds. The cycle time (C) thus equals:

C = Total available time / Units needed

Therefore,

C = 3600 seconds / 180 units = 20 seconds per unit

This means each PDA must be completed within 20 seconds to meet the hourly production goal.

Theoretical Minimum Number of Workstations

The total task time is the sum of all individual tasks:

  • A: 12 sec
  • B: 15 sec
  • C: 8 sec
  • D: 5 sec
  • E: 20 sec

Sum of task times = 12 + 15 + 8 + 5 + 20 = 60 seconds

The minimum number of workstations (N) is obtained by dividing total task time by cycle time:

N = Total task time / Cycle time = 60 / 20 = 3

Since a fractional workstation isn't feasible, the minimum number of workstations is 3.

Practical Line Balancing and Assignments

While the theoretical minimum suggests 3 workstations, practical constraints such as task precedence and balancing may prevent achieving this exact number. Assigning tasks to match the cycle time involves grouping tasks into workstations without violating precedence and ensuring that total task times per workstation do not exceed 20 seconds.

For example, a feasible assignment could be:

Workstation 1:

  • Task A (12 seconds)
  • Task C (8 seconds)

(Total time: 20 seconds)

Workstation 2:

  • Task B (15 seconds)

Remaining tasks:

Workstation 3:

  • Task D (5 seconds)
  • Task E (20 seconds)

This assignment respects task precedence and cycle time limits, even if it leads to some inefficiencies and idle times.

Conclusion

Efficient line balancing is essential for meeting production goals while minimizing costs. The calculated cycle time of 20 seconds and minimum workstation number of 3 provide a baseline. Practical application may require adjustments to task assignments to accommodate precedence constraints and optimize throughput. Continuous evaluation and process improvements are necessary for attaining an optimal balance between theoretical targets and real-world constraints.

References

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  • Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2006). Operations Management for Competitive Advantage (11th ed.). McGraw-Hill.
  • Slack, N., Chambers, S., & Johnston, R. (2010). Operations Management (6th ed.). Pearson Education.
  • Mahadevan, B. (2015). Operations Management: Theory and Practice. Pearson.
  • Shingo, S. (1989). A Study of the Toyota Production System. Routledge.
  • Goldratt, E. M., & Fox, J. (1986). The Goal: A Process of Ongoing Improvement. North River Press.
  • Stevenson, W. J. (2012). Operations Management (11th ed.). McGraw-Hill Education.
  • Akturk, M., & Haghparast, M. (2020). Line Balancing and Optimization Approaches: A Review. International Journal of Production Economics, 227, 107613.
  • Ordoñez, J., & Pereira, A. (2017). Assembly Line Balancing: Methods and Applications. Procedia Manufacturing, 21, 410–417.
  • Shtub, A., & Karni, R. (2017). Project Management: Engineering, Technology, and Implementation. Pearson.

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