An Analysis on the Dynamics of Work in Process (WIP) in a High Volume Manufacturing System of a Semiconductor Company Using System Dynamics

Dennis T. Beng Hui

Department of Industrial Engineering, College of Engineering De La Salle University-Manila, 2401 Taft Avenue, Malate, Manila

dennis.benghui@dlsu.edu.ph Abstract – High volume manufacturing (HVM) typically uses a push system to prioritize throughput, but inadvertently promote the growth of WIP. Part of an HVM is the presence of re-entrants resulting to the explosion of outputs coming from a single input. Such is the case of the Slider Manufacturing Process. Keywords— Dynamic Work-in-Process, System Dynamics, Simulation, High Volume Manufacturing

I. INTRODUCTION

A High Volume Manufacturing (HVM) set up is defined in this paper as a manufacturing process engaged in the production of almost homogenous set of products where the production network is composed of “nested loops of re-entrant processes and low yield due to imperfect equipment”[1].

These manufacturing processes are typically used to make products that are considered fundamental consumer needs and thus expected to match the output of a traditional mass manufacturing system. One type of product that an HVM set up is compatible to is the need to manufacturing and assemble data storage devices. A few of the known companies in the Philippines involved in manufacture/assembly of data storage devices are Hitachi GST Philippines (HICAP), TDK-Fujitsu, and Toshiba Philippines. Figure 1 below shows a typical design of a storage device (www.visualdictionaryo.com).

Fig. 1 Example of Storage Device Component

II. SLIDER MANUFACTURING SET-UP

The focus of this paper is on the manufacturing processes of a “slider” which is a critical component in the head of a storage device. The slider allows the storage device to perform the read and write functions. The manufacturing process of a slider involves more than a hundred processes starting from the cutting of the wafer into Quad to a Row Bar up to a Slider. Figure 2 shows the conversion from Quad to Slider.

Fig. 2 Conversion from Quad to Slider

When cutting the Quad into row bars, the Quad undergoes a re-entrant process where each row bar in a Quad undergoes a lapping and cutting process. Similarly, the Row Bar eventually goes through a re-entrant process where each Slider is cut from the row bar. The paper will not discuss the technical properties and operation in the transformation of the Quad to the slider. Suffice it to say, that re-entrant activities are built into the Slider Manufacturing Process especially in the slicing/cutting of the Row Bar from the Quad, and the Slider from the Row Bar. The re-entrant processes are shown in figure 3.

Fig. 3 Conversion from Quad to Slider

III. CAUSAL LOOP DIAGRAM

More than the physical and technical properties of the manufacturing processes are the observed relationships between the following indicators critical in the management of the slider manufacturing process or any mass manufacturing

system for that matter. These are Work-in-Process (WIP), Throughput (TP), and Lead Time (LT). The causal relationship of the following variables can be seen in figure 4 below.

Fig. 4 Causal Relationship of WIP, LT, and TP

The causal relationship above shows the presence of 3 positive feedback loops, which indicates that the value of WIP will be accumulating. This means that WIP is expected to build up in any manufacturing process. This concept basically follows the principle of Little’s Law [2].

Little’s Law states that L is average amount of items in queue, W are the average waiting time per item, and Lambda is the arrival rate of the units. The same Little’s law has been used to explain the relationship between the three variables shown above [3]. The equivalent notation is expressed as follows: Where L = WIP, Lambda = TP, and W = LT.

However, in practice, WIP although accumulates eventually goes down. What exists is the presence of adjustments in releasing work into the manufacturing process. The Release rate, in this case the release of Wafer into the Slider Manufacturing Process, is being regulated based on the expected slider output against that of the actual output. Thus, the unbridle accumulation of WIP is in a way being regulated.

Another complicated condition in the Slider

Manufacturing Process is the presence the explosion of components from a single input item resulting from the re-entrant activities. This adds into the dilemma of reinforcing growth in our WIP.

In practice, it can be observed that WIP is often less prioritized over throughput. This common perception of prioritizing WIP over TP often leads to the practice of pull manufacturing, where items are always loaded into the manufacturing process [4] regardless of the WIP.

IV. STOCK FLOW DIAGRAM

A system dynamics model is constructed using the basic stock and flow diagram (SFD) introduced by Jay Forrester from MIT. The resulting SFD for the high volume manufacturing with re-entrants and explosion of outputs are shown in figure 5.

Fig. 5 Stock Flow Diagram for 3 Process Level HVM

with re-entrants. The re-entrants in the SFD were modeled using a delay

command to indicate that the entire output of a single input will be completed upon the completion of the re-entrants. Re-entrants are expressed as time based units in order to reflect the period when the re-entrant processes have been completed and thus the transfer of outputs as well.

When the re-entrant process is on-going, partial output

items are already transferred to the next WIP level, thus promoting a push like system as what is happening in practice. The basic form of managing the WIP is the inclusion of a flushing activity represented by the regulated release rate situated at the beginning of the manufacturing process.

Each WIP level represents the buffer area in between

processes, while the process rates represent the processing areas where inputs are converted into multiple outputs.

Release rate ofjobs/materials to

production

Average WIP in system(Jobs in the system)

Process Utilization(% busy)

Average Leadtime (fromrelease time to completion

time)

Actual AverageThroughput (Output

rate)

Gap (Release rate -Output rate)

+

+

+

+

+

-

-

-

WL λ=

LTWIPTP

thusTPxLTWIP

=

=,

V. SIMULATION RESULTS The resulting SFD were analyzed by changing the

parameters of the model and running the simulation for a total of 100 hours.

A. Uniform Re-entrant Processes When the re-entrant processes are small and relatively

similarly in ratio across the three processing rates, the system tends to achieve equilibrium over time because of the presence of a regulated release rate which was not captured in the causal loop diagram. This is shown in the figures below.

Fig. 6 Pattern of WIP from three buffer areas

Fig. 7 Pattern of Release and Processing Rates

The results show that changing the processing time,

WIP levels, and other operational parameters results to a leveling of performances across the WIP and Throughput.

Lead Time was expressed as processing time and that

the processing time is interpreted as the total processing time of a given input, which includes the processing of multiple outputs. Re-entrant time is represented as delay and is also the same as the multiple outputs for each process rates. It can be noticed that the release rate has lower value compared to the processing rates since the input value is actually factored by a multiplier that would represent the multiple outputs in each of the process rates.

B. Asynchronous Re-entrant Processes The basic concern right now is “what makes this type of

manufacturing process behave in an oscillating manner?” This can be observed when the presence of delay across

the three processing is asynchronous. This means that the highest delay values are at least 3 times larger than that of the lowest delay values.

This means that delays are interpreted to not only

represent re-entrant activities, but delay in the handling of information from the processing area to the release rate. The following figure below shows the oscillating pattern when one of the processing rates experience 3 times delay over the rest of the processing rates.

Fig. 8 Oscillating Pattern of WIP from three buffer areas

Fig. 9 Oscillating Pattern of Processing Rates from three

buffer areas It can be seen that the oscillations are more prominent and

that equilibrium will take longer to achieve even when the expected output per period remains the same.

VI. CONCLUSION

High Volume Manufacturing is thought of as a simple

and straightforward environment for managing WIP. However, it seems that from the system dynamics simulation that even by isolating the other parameters of the manufacturing environment, except for the presence of re-entrants and information delays to the release rate (which acts as a regulator of the process) do make a significant impact on whether the process will oscillate or not.

The significance of the dynamic nature of WIP in a high volume manufacturing set-up is largely influenced by the presence of unbalanced re-entrant process and untimely production and WIP information which affirms the problems that are currently being experienced by these semiconductor companies.

References: [1] Y. Nonaka, Y. Suginishi, A. Lengyel, M. Ono, and K. Sugimoto, "TSUNAMI Effect Prediction Methodology for Critical Resource Analysis," in Manufacturing Systems and Technologies for the New Frontier, 2008, pp. 337-340. [2] M. F. Ramalhoto, J. A. Amaral, and M. T. Cochito, "A Survey of J. Little's Formula," International Statistical Review / Revue Internationale de Statistique, vol. 51, pp. 255-278, 1983. [3] W. J. Hopp and M. L. Spearman, Factory Physics: McGraw Hill, 1995. [4] M. L. Spearman and M. A. Zazanis, "Push and Pull Production Systems: Issues and Comparisons," Operations Research, vol. 40, pp. 521-532, 1992.