Evaluating Capacity

2.1. Traditional Operational Availability Model

Toyota Motor Corporation (Toyota) is known for setting the standard in manufacturing industries for producing products in the fastest and most efficient way because of the Toyota Production System (TPS). When Toyota builds a plant in Japan or abroad, TPS has been implemented to optimize the production process. It has successfully reduced manufacturing lead times, reduced work in process, and improved work environment and manufacturing operation.

On the other hands, the throughput is primary oriented toward the reduction of time required by the manufacturing process, so that the profitability can be increased. With TPS, the throughput of each step is closely connected together because of reduced inventory. A primary objective of TPS is to achieve smooth continuous flow. It is very important to identify and improve the throughput bottleneck step to improve TPS operation flow.

One main metrics of throughput evaluation is operational availability (OA). In TPS, the operational availability is defined as the probability that a system is ready to perform its mission or how well the product and process satisfies end user demands.

In traditional operational availability model, the overall throughput of a system is calculated at last step (step 4 as shown in Figure 1). However, it cannot be seen the article about the processing capacity improvement in consideration of the sequential system aspect each other.

Figure 1. Traditional Operational Availability Model

Figure 2. New Japanese Production System Model, Advanced TPS

2.2. Necessity of New Operational Availability Model

This operational availability model, as shown in Equation (1), can also be applied to evaluate each step operation status. Although the OA is a good indicator to show the throughput of the plant or even each step, it is difficult to analyze the bottleneck or to understand the reason behind the OA issues. The throughput can be affected by equipment or production issue, furthermore, short time (starvation) and full time (blockage) and other reasons. It is easy to track issues at each step but hard to judge the impact through each step to overall throughput.

The importance of quantifying elements for the manufacturing plant is to find areas for improvement. For example, if the overall OA is 92% and the OA target is 98% then the gap is 6%. If we know the 90% OA gap is due to equipment and 10% OA gap is due to production repair, the opportunity to close the OA gap for improving equipment is usually much greater than for improving production repair.

In order to accomplish TPS smooth floor, the authors have proposed a new production operational availability model to evaluate production throughput to pinpoint where to make improvements in consideration of the work delay, maintenance of facilities and the influence of sequential system aspect each other. It also helps to standardize the throughput evaluation process for global production.

$O A= \frac{\text { Production Time-Short Time-Equipment Time-Work Delay Time }}{\text { Production Time }} \times 100\%$

2.3. Proposal of Advanced TPS for Global Production

Given this background, the authors have recognized the necessity for advancement of Japanese production management system methodologies and therefore hereby propose "Advanced TPS" as shown in Fig. 2. Advanced TPS is meant as a methodology to attain high quality assurance in global production. Advanced TPS is comprised of four different pillars: Productivity, Cost, Workability, and Quality. This proposal focuses on the pillar of productivity by implementing a system which will be able to improve and maintain efficient inventory management throughout the plant. Today we will describe the inventory management subject which is mainly in relation with the cost and productivity pillars of Advanced TPS.

3.1. Strategic Development of the New Operational Availability Model

In TPS, the inventory buffer between each step is low so the overall impact of all previous steps affects the final throughput through short time (manufacturing starvation) to following step. Each step also affects the throughput of previous steps through full time (manufacturing blockage). The impact of each step or certain type of downtime can be evaluated by analyzing relationships between the so-called manufacturing blockage (Full) and manufacturing starvation (Short) of each step, as shown in Fig. 3.

Figure 3. Proposed Operational Availability Model

The throughput contribution factor of any step in the whole production line, from first step to last step, can be quantified. This evaluation method can be utilized with historical data for productivity improvement as well as real time data for floor management (real time bottleneck visual display). This model can be applied for one production line, as well as one plant or between plants and supplier.

3.2. Development of New Operational Availability Model to Link the Impact from One Step to Following Step

The authors have proposed a method to link throughput impact between steps, as shown in Fig. 4. The impact of any step to following step is consisted of two parts: The one is introduced by this step and the one is inherited from previous step. In this model, each impact factor to following step is calculated proportionally. The inherited impact of Step 3 to Step 4 is calculated in Equation (2). The introduced impact from Step 3 to Step 4 is calculated in Equation (3). The impact from each different downtime causes of this step is also can be quantified individually. Equation (4) and (5) show how to calculate equipment downtime impact and work delay impact from Step 3 to Step 4.

Figure 4. Model to link impact between two steps

$inherited\ Impact = \frac{ST3}{ST3+WT3+ET3} \times ST4$

$WT3$ is work delay at Step 3

$ET3$ is equipment downtime at Step 3

$ST4$ is Short time to Step 4 from Step 3

$Introduced\ Impact = \frac{WT3+ET3}{ST3+WT3+ET3} \times ST4$

$Introduce\ Impact\ due\ to\ Equipment\ = \frac{ET3}{ST3+WT3+ET3} \times ST4$

$Introduce\ Impact\ due\ to\ Work\ Delay\ = \frac{WT3}{ST3+WT3+ET3} \times ST4$

Based on this model which links impact between steps, the impact of each step to whole system with multiple steps can be developed. The calculation is applicable to large or small scale systems.

We have applied for new operational availability model into Toyota in U.S.A. (Toyota USA) with a 4 step system as shown in Fig. 5.

Figure 5. Model to link impact of multiple Steps

Inherited Impact of Step 2=$\frac{\text { ST2 }}{\text { ST2+WT2+ET2 }} \times \frac{S T 3}{S T 3+W T 3+E T 3} \times S T 4$

Where $ST2$ is Short time to Step 2 from previous steps.

$WT2$ is work delay at Step 2

$ET2$ is equipment downtime at Step 2

$ST2$ is Short time to Step 3 from Step 2

Introduced Impact of Station 2=$\frac{W T 2+E T 2}{S T 2+W T 2+E T 2} \times \frac{W T 3+E T 3}{S T 3+W T 3+E T 3} \times S T 4$

Inherited Impact of Step 1= $\frac{S T 1}{S T 1+W T 1+E T 1} \times \frac{S T 2}{S T 2+W T 2+E T 2} \times \frac{S T 3}{S T 3+W T 3+E T 3} \times S T 4$

$E T 1$ is equipment downtime at Step 1

$S T 1$ is Short time to Step 2 from Step 1

Introduced Impact of Station $1=\frac{W T 1+E T 1}{S T 1+W T 1+E T 1} \times \frac{S T 2}{S T 2+W T 2+E T 2} \times \frac{S T 3}{S T 3+W T 3+E T 3} \times S T 4$

$E S=\frac{\frac{\frac{E T 1}{S T 1+W T 1+E T 1} \times S T 2+E T 2}{S T 2+W T 2+E T 2} \times S T 3+E T 3}{S T 3+W T 3+E T 3} \times S T 4+E T 4$

$E s$ is the overall equipment impact to the system shown in Fig.5.

$E O A=\frac{\text { Production Time-Es }}{\text { Production Time }} \times 100 \%$

$E O A$ is the Equipment $\mathrm{OA}$ of the overall system shown in Fig.5.

$W O A=\frac{\text { Production Time-Ws }}{\text { Production Time }} \times 100 \%$

$WOA$ is the Work Delay $OA$ of the overall system shown in Fig.5.