SA5_DVT_OQC_Stat.Rmd

---
title: "PQE SA5 DVT OQC Data Summary"
author: "Colin Chen"
date: "2022-08-17"
output: html_document
---

## Abstract

This particular report emphasizes on the OQC results for the DVT Bikes, PQE have logged *262* DVT bikes across three different contracted manufacturers (CM) from TConn, Ideal and Speedtech.

The detailed DVT bikes which were OQCed at the CM site are as follows:
```{R Table Summary Distribution, include = FALSE, warning = FALSE}
total_qty <- c(222, 15, 25)
names(total_qty) <- c("TConn", "Ideal", "Speedtech")
```

```{R Show Table Summary, include = TRUE}
total_qty
```

The latter section will be split into preliminary data setup, then the display of yield rate distribution and visualized distribution for the pass/fail fraction.

```{R Library Loading, include = FALSE, warning = FALSE}
# Read Necessary Library

library(readr)
library(tidyverse)
library(kableExtra)
library(plotly)
```

```{R Data Filtering, include = FALSE, warning = FALSE}
# Import Summary
oqc_df <- read_csv("SA5_DVT_OQC.csv", col_names = TRUE, col_types = "ccccccci")

# Filter Overall Statistics from the data table
oqc_overall <- oqc_df %>%
  filter(CM == "Overall") 

# Breakdown to Overall Static and Dynamic Test Result
overall_static <- oqc_overall %>%
  filter(Inspection_Style == "Static") %>%
  mutate(Percent = round(Qty/262*100,2))

overall_dynamic <- oqc_overall %>%
  filter(Inspection_Style == "Dynamic") %>%
  mutate(Percent = round(Qty/262*100,2))

# Filter TConn Statistics from the data table
oqc_tconn <- oqc_df %>%
  filter(CM == "TConn") 

# Breakdown to TConn Static and Dynamic Test Result
tconn_static <- oqc_tconn %>%
  filter(Inspection_Style == "Static") %>%
  mutate(Percent = round(Qty/222*100,2))

tconn_dynamic <- oqc_tconn %>%
  filter(Inspection_Style == "Dynamic") %>%
  mutate(Percent = round(Qty/222*100,2))

# Filter Ideal Statistics from the data table
oqc_ideal <- oqc_df %>%
  filter(CM == "Ideal") 

# Breakdown to Ideal Static and Dynamic Test Result
ideal_static <- oqc_ideal %>%
  filter(Inspection_Style == "Static") %>%
  mutate(Percent = round(Qty/15*100,2))

ideal_dynamic <- oqc_ideal %>%
  filter(Inspection_Style == "Dynamic") %>%
  mutate(Percent = round(Qty/15*100,2))

# Filter Speedtech Statistics from the data table
oqc_speedtech <- oqc_df %>%
  filter(CM == "Speedtech") 

# Breakdown to Ideal Static and Dynamic Test Result
speedtech_static <- oqc_speedtech %>%
  filter(Inspection_Style == "Static") %>%
  mutate(Percent = round(Qty/25*100,2))

speedtech_dynamic <- oqc_speedtech %>%
  filter(Inspection_Style == "Dynamic") %>%
  mutate(Percent = round(Qty/25*100,2))
```

## Inspection Item Description

For the OQC inspection items, the component type will be split into `Mechanical` and `Eletrical` for the classification. And the aspects will be split into `Function`, `Cosmetics` and `Safety`. Lastly, the inspection style will also be split as `Static` and `Dynamic`.

Therefore, for individual OQC items, there will be split into the following pseudo code rule.

e.g SF01 where `S` means Static inspection style, `F` means Function and `01` is the 1st serial item. 


## Cumulative DVT OQC Statistics

This section will summarize cumulative data based on all 3 CMs, the following code will illustrate the brief % of pass, fail and did not inspect (DNI)% for both static and dynamic test for DVT bikes.

```{r Cumulative Static Data Summary, include = FALSE}
# Summarize the data frame
SF01_Overall <- overall_static$Percent[1:3]
SF02_Overall <- overall_static$Percent[4:6]
SF03_Overall <- overall_static$Percent[7:9]
SC01_Overall <- overall_static$Percent[10:12]
SC02_Overall <- overall_static$Percent[13:15]
SF04_Overall <- overall_static$Percent[16:18]
SC02_Overall <- overall_static$Percent[19:21]
SC03_Overall <- overall_static$Percent[22:24]
SS01_Overall <- overall_static$Percent[25:27]
SF05_Overall <- overall_static$Percent[28:30]
SF06_Overall <- overall_static$Percent[31:33]
SF07_Overall <- overall_static$Percent[34:36]
SF08_Overall <- overall_static$Percent[37:39]
SC04_Overall <- overall_static$Percent[40:42]
SC05_Overall <- overall_static$Percent[43:45]
SC06_Overall <- overall_static$Percent[46:48]
SC07_Overall <- overall_static$Percent[49:51]
SC08_Overall <- overall_static$Percent[52:54]
SF09_Overall <- overall_static$Percent[55:57]

overall_static_sum <- rbind.data.frame(SF01_Overall,
                                 SF02_Overall,
                                 SF03_Overall,
                                 SC01_Overall,
                                 SC02_Overall,
                                 SF04_Overall,
                                 SC02_Overall,
                                 SC03_Overall,
                                 SS01_Overall,
                                 SF05_Overall,
                                 SF06_Overall,
                                 SF07_Overall,
                                 SF08_Overall,
                                 SC04_Overall,
                                 SC05_Overall,
                                 SC06_Overall,
                                 SC07_Overall,
                                 SC08_Overall,
                                 SF09_Overall)

colnames(overall_static_sum) <- c("Overall Pass %", "Overall Fail %", "Overall DNI %")
rownames(overall_static_sum) <- c("Front Light (SF01)",
                                  "Rear Light (SF02)",
                                  "LED Ring (SF03)",
                                  "Frame Noise (SC01)",
                                  "Handlebar Cosmetics (SC02)",
                                  "Kickstand Noise (SF04)",
                                  "E-Shifter Plug Cosmetics (SC02)",
                                  "Charger Plug Cosmetics (SC03)",
                                  "Brake Tube (SS01)",
                                  "Battery Function (SF05)",
                                  "Kicklock Function (SF06)",
                                  "Main ECU (SF07)",
                                  "Horn Function (SF08)",
                                  "Frame Cosmetics (SC04)",
                                  "Front Fork Cosmetics (SC05)",
                                  "Front Fender Cosmetics (SC06)",
                                  "Rear Fender Cosmetics (SC07)",
                                  "Handlebar Grip Gap (SC08)",
                                  "Assistance Level Change (SF09)")
```

```{R Overall Static Table, warning = FALSE, include = TRUE}
# Make it as a kable
kable(overall_static_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 1, include = FALSE, warning = FALSE}
# Remove additional variables
rm(SF01_Overall, 
   SF02_Overall,
   SF03_Overall,
   SC01_Overall,
   SC02_Overall, 
   SF04_Overall,
   SC02_Overall,
   SC03_Overall,
   SS01_Overall,
   SF05_Overall,
   SF06_Overall,
   SF07_Overall,
   SF08_Overall,
   SC04_Overall,
   SC05_Overall,
   SC06_Overall,
   SC07_Overall,
   SC08_Overall,
   SF09_Overall)
```

```{R Cumulative Static Graph Setup, echo = TRUE, include = FALSE}
# Graph Static Overview
static_1 <- overall_static %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") +
  labs(x = "Inspection Item", y = "Percent Fraction", title = "SA5 DVT Overall Static QQC Distribution")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R Overall Static Graph Demo}
ggplotly(static_1)
```

```{R Cumulative Dynamic Data Summary, warning = FALSE, include = FALSE}
# Summarize the data frame
DS01_Overall <- overall_dynamic$Percent[1:3]
DF01_Overall <- overall_dynamic$Percent[4:6]
DF02_Overall <- overall_dynamic$Percent[7:9]
DF03_Overall <- overall_dynamic$Percent[10:12]
DF04_Overall <- overall_dynamic$Percent[13:15]
DS02_Overall <- overall_dynamic$Percent[16:18]
DF05_Overall <- overall_dynamic$Percent[19:21]
DF06_Overall <- overall_dynamic$Percent[22:24]
DF07_Overall <- overall_dynamic$Percent[25:27]
DF08_Overall <- overall_dynamic$Percent[28:30]

overall_dynamic_sum <- rbind.data.frame(DS01_Overall,
                                 DF01_Overall,
                                 DF02_Overall,
                                 DF03_Overall,
                                 DF04_Overall,
                                 DS02_Overall,
                                 DF05_Overall,
                                 DF06_Overall,
                                 DF07_Overall,
                                 DF08_Overall)

colnames(overall_dynamic_sum) <- c("Overall Pass %", "Overall Fail %", "Overall DNI %")
rownames(overall_dynamic_sum) <- c("Brake System (DS01)",
                                  "BB Sensor (DF01)",
                                  "Front Brake Disc Noise (DF02)",
                                  "Rear Brake Disc Noise (DF03)",
                                  "Chain Guard Issue (DF04)",
                                  "Wheelset Wobble (DS02)",
                                  "Dynamic E-Shifter Gear Shifting (DF05)",
                                  "Motor (DF06)",
                                  "Kicklock Noise (DF07)",
                                  "Rear Hub Noise (DF08)")
```

```{R Overall Dynamic Table, warning = FALSE, include = TRUE}
# Make it as a kable
kable(overall_dynamic_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 2, include = FALSE, warning = FALSE}
# Remove additional variables to save space
rm(DS01_Overall,
   DF01_Overall, 
   DF02_Overall,
   DF03_Overall,
   DF04_Overall,
   DS02_Overall,
   DF05_Overall,
   DF06_Overall,
   DF07_Overall,
   DF08_Overall)
```

```{R Cumulative Dynamic Graph Setup, echo = TRUE, include = FALSE}
# Graph Dynamic Overview
dynamic_1 <- overall_dynamic %>%
  mutate(Percent = round(Qty/262*100,2)) %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") + 
    labs(x = "Inspection Item", y = "Percentage Fraction", title = "SA5 DVT Overall Dynamic QQC Distribution")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R Overall Dynamic Graph Demo}
ggplotly(dynamic_1)
```

## TConn DVT OQC Statistics.

This section will summarize data from TConn, the following code will illustrate the brief % of pass, fail and did not inspect (DNI)% for both static and dynamic test for DVT bikes.

```{r TConn Static Data Summary, include = FALSE, warning = FALSE}
# Summarize the data frame
SF01_tconn <- tconn_static$Percent[1:3]
SF02_tconn <- tconn_static$Percent[4:6]
SF03_tconn <- tconn_static$Percent[7:9]
SC01_tconn <- tconn_static$Percent[10:12]
SC02_tconn <- tconn_static$Percent[13:15]
SF04_tconn <- tconn_static$Percent[16:18]
SC02_tconn <- tconn_static$Percent[19:21]
SC03_tconn <- tconn_static$Percent[22:24]
SS01_tconn <- tconn_static$Percent[25:27]
SF05_tconn <- tconn_static$Percent[28:30]
SF06_tconn <- tconn_static$Percent[31:33]
SF07_tconn <- tconn_static$Percent[34:36]
SF08_tconn <- tconn_static$Percent[37:39]
SC04_tconn <- tconn_static$Percent[40:42]
SC05_tconn <- tconn_static$Percent[43:45]
SC06_tconn <- tconn_static$Percent[46:48]
SC07_tconn <- tconn_static$Percent[49:51]
SC08_tconn <- tconn_static$Percent[52:54]
SF09_tconn <- tconn_static$Percent[55:57]

tconn_static_sum <- rbind.data.frame(SF01_tconn,
                                 SF02_tconn,
                                 SF03_tconn,
                                 SC01_tconn,
                                 SC02_tconn,
                                 SF04_tconn,
                                 SC02_tconn,
                                 SC03_tconn,
                                 SS01_tconn,
                                 SF05_tconn,
                                 SF06_tconn,
                                 SF07_tconn,
                                 SF08_tconn,
                                 SC04_tconn,
                                 SC05_tconn,
                                 SC06_tconn,
                                 SC07_tconn,
                                 SC08_tconn,
                                 SF09_tconn)

colnames(tconn_static_sum) <- c("TConn Pass %", "TConn Fail %", "TConn DNI %")
rownames(tconn_static_sum) <- c("Front Light (SF01)",
                                  "Rear Light (SF02)",
                                  "LED Ring (SF03)",
                                  "Frame Noise (SC01)",
                                  "Handlebar Cosmetics (SC02)",
                                  "Kickstand Noise (SF04)",
                                  "E-Shifter Plug Cosmetics (SC02)",
                                  "Charger Plug Cosmetics (SC03)",
                                  "Brake Tube (SS01)",
                                  "Battery Function (SF05)",
                                  "Kicklock Function (SF06)",
                                  "Main ECU (SF07)",
                                  "Horn Function (SF08)",
                                  "Frame Cosmetics (SC04)",
                                  "Front Fork Cosmetics (SC05)",
                                  "Front Fender Cosmetics (SC06)",
                                  "Rear Fender Cosmetics (SC07)",
                                  "Handlebar Grip Gap (SC08)",
                                  "Assistance Level Change (SF09)")
```

```{R TConn Static Table, include = TRUE, warning = FALSE}
# Make it as a kable
kable(tconn_static_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 3, include = FALSE, warning = FALSE}
# Remove additional variables
rm(SF01_tconn, 
   SF02_tconn,
   SF03_tconn,
   SC01_tconn,
   SC02_tconn, 
   SF04_tconn,
   SC02_tconn,
   SC03_tconn,
   SS01_tconn,
   SF05_tconn,
   SF06_tconn,
   SF07_tconn,
   SF08_tconn,
   SC04_tconn,
   SC05_tconn,
   SC06_tconn,
   SC07_tconn,
   SC08_tconn,
   SF09_tconn)
```

```{R TConn Static Graph Setup, echo = TRUE, include = FALSE}
# Graph Static Overview
static_2 <- tconn_static %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") +
  labs(x = "Inspection Item", y = "Percent Fraction", title = "SA5 DVT TConn Static QQC Summary")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R TConn Static Graph Demo}
ggplotly(static_2)
```

```{R TConn Dynamic Data Summary, include = FALSE, warning = FALSE}
# Summarize the data frame
DS01_tconn <- tconn_dynamic$Percent[1:3]
DF01_tconn <- tconn_dynamic$Percent[4:6]
DF02_tconn <- tconn_dynamic$Percent[7:9]
DF03_tconn <- tconn_dynamic$Percent[10:12]
DF04_tconn <- tconn_dynamic$Percent[13:15]
DS02_tconn <- tconn_dynamic$Percent[16:18]
DF05_tconn <- tconn_dynamic$Percent[19:21]
DF06_tconn <- tconn_dynamic$Percent[22:24]
DF07_tconn <- tconn_dynamic$Percent[25:27]
DF08_tconn <- tconn_dynamic$Percent[28:30]

tconn_dynamic_sum <- rbind.data.frame(DS01_tconn,
                                 DF01_tconn,
                                 DF02_tconn,
                                 DF03_tconn,
                                 DF04_tconn,
                                 DS02_tconn,
                                 DF05_tconn,
                                 DF06_tconn,
                                 DF07_tconn,
                                 DF08_tconn)

colnames(tconn_dynamic_sum) <- c("TConn Pass %", "TConn Fail %", "TConn DNI %")
rownames(tconn_dynamic_sum) <- c("Brake System (DS01)",
                                  "BB Sensor (DF01)",
                                  "Front Brake Disc Noise (DF02)",
                                  "Rear Brake Disc Noise (DF03)",
                                  "Chain Guard Issue (DF04)",
                                  "Wheelset Wobble (DS02)",
                                  "Dynamic E-Shifter Gear Shifting (DF05)",
                                  "Motor (DF06)",
                                  "Kicklock Noise (DF07)",
                                  "Rear Hub Noise (DF08)")
```

```{R TConn Dynamic Table, include = TRUE, warning = FALSE}
# Make it as a kable
kable(tconn_dynamic_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 4, include = FALSE, warning = FALSE}
# Remove additional variables to save space
rm(DS01_tconn,
   DF01_tconn, 
   DF02_tconn,
   DF03_tconn,
   DF04_tconn,
   DS02_tconn,
   DF05_tconn,
   DF06_tconn,
   DF07_tconn,
   DF08_tconn)
```

```{R TConn Dynamic Graph Distribution, echo = TRUE, include = FALSE}
# Graph Dynamic Overview
dynamic_2 <- tconn_dynamic %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") + 
    labs(x = "Inspection Item", y = "Percentage Fraction", title = "SA5 DVT TConn Dynamic QQC Summary")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R TConn Dynamic Graph Demo}
ggplotly(dynamic_2)
```

## Ideal DVT OQC Statistics.

This section will summarize data from Ideal, the following code will illustrate the brief % of pass, fail and did not inspect (DNI)% for both static and dynamic test for DVT bikes.

```{r Ideal Static Data Summary, include = FALSE, warning = FALSE}
# Summarize the data frame
SF01_ideal <- ideal_static$Percent[1:3]
SF02_ideal <- ideal_static$Percent[4:6]
SF03_ideal <- ideal_static$Percent[7:9]
SC01_ideal <- ideal_static$Percent[10:12]
SC02_ideal <- ideal_static$Percent[13:15]
SF04_ideal <- ideal_static$Percent[16:18]
SC02_ideal <- ideal_static$Percent[19:21]
SC03_ideal <- ideal_static$Percent[22:24]
SS01_ideal <- ideal_static$Percent[25:27]
SF05_ideal <- ideal_static$Percent[28:30]
SF06_ideal <- ideal_static$Percent[31:33]
SF07_ideal <- ideal_static$Percent[34:36]
SF08_ideal <- ideal_static$Percent[37:39]
SC04_ideal <- ideal_static$Percent[40:42]
SC05_ideal <- ideal_static$Percent[43:45]
SC06_ideal <- ideal_static$Percent[46:48]
SC07_ideal <- ideal_static$Percent[49:51]
SC08_ideal <- ideal_static$Percent[52:54]
SF09_ideal <- ideal_static$Percent[55:57]

ideal_static_sum <- rbind.data.frame(SF01_ideal,
                                 SF02_ideal,
                                 SF03_ideal,
                                 SC01_ideal,
                                 SC02_ideal,
                                 SF04_ideal,
                                 SC02_ideal,
                                 SC03_ideal,
                                 SS01_ideal,
                                 SF05_ideal,
                                 SF06_ideal,
                                 SF07_ideal,
                                 SF08_ideal,
                                 SC04_ideal,
                                 SC05_ideal,
                                 SC06_ideal,
                                 SC07_ideal,
                                 SC08_ideal,
                                 SF09_ideal)

colnames(ideal_static_sum) <- c("Ideal Pass %", "Ideal Fail %", "Ideal DNI %")
rownames(ideal_static_sum) <- c("Front Light (SF01)",
                                  "Rear Light (SF02)",
                                  "LED Ring (SF03)",
                                  "Frame Noise (SC01)",
                                  "Handlebar Cosmetics (SC02)",
                                  "Kickstand Noise (SF04)",
                                  "E-Shifter Plug Cosmetics (SC02)",
                                  "Charger Plug Cosmetics (SC03)",
                                  "Brake Tube (SS01)",
                                  "Battery Function (SF05)",
                                  "Kicklock Function (SF06)",
                                  "Main ECU (SF07)",
                                  "Horn Function (SF08)",
                                  "Frame Cosmetics (SC04)",
                                  "Front Fork Cosmetics (SC05)",
                                  "Front Fender Cosmetics (SC06)",
                                  "Rear Fender Cosmetics (SC07)",
                                  "Handlebar Grip Gap (SC08)",
                                  "Assistance Level Change (SF09)")
```

```{R Ideal Static Table, include = TRUE, warning = FALSE}
# Make it as a kable
kable(ideal_static_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 5, include = FALSE, warning = FALSE}
# Remove additional variables
rm(SF01_ideal, 
   SF02_ideal,
   SF03_ideal,
   SC01_ideal,
   SC02_ideal, 
   SF04_ideal,
   SC02_ideal,
   SC03_ideal,
   SS01_ideal,
   SF05_ideal,
   SF06_ideal,
   SF07_ideal,
   SF08_ideal,
   SC04_ideal,
   SC05_ideal,
   SC06_ideal,
   SC07_ideal,
   SC08_ideal,
   SF09_ideal)
```

```{R Ideal Static Graph Setup, echo = TRUE, include = FALSE}
# Graph Static Overview
static_3 <- ideal_static %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") +
  labs(x = "Inspection Item", y = "Percent Fraction", title = "SA5 DVT Ideal Static QQC Summary")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R Ideal Static Graph Demo}
ggplotly(static_3)
```

```{R Ideal Dynamic Data Summary, include = FALSE, warning = FALSE}
# Summarize the data frame
DS01_ideal <- ideal_dynamic$Percent[1:3]
DF01_ideal <- ideal_dynamic$Percent[4:6]
DF02_ideal <- ideal_dynamic$Percent[7:9]
DF03_ideal <- ideal_dynamic$Percent[10:12]
DF04_ideal <- ideal_dynamic$Percent[13:15]
DS02_ideal <- ideal_dynamic$Percent[16:18]
DF05_ideal <- ideal_dynamic$Percent[19:21]
DF06_ideal <- ideal_dynamic$Percent[22:24]
DF07_ideal <- ideal_dynamic$Percent[25:27]
DF08_ideal <- ideal_dynamic$Percent[28:30]

ideal_dynamic_sum <- rbind.data.frame(DS01_ideal,
                                 DF01_ideal,
                                 DF02_ideal,
                                 DF03_ideal,
                                 DF04_ideal,
                                 DS02_ideal,
                                 DF05_ideal,
                                 DF06_ideal,
                                 DF07_ideal,
                                 DF08_ideal)

colnames(ideal_dynamic_sum) <- c("Ideal Pass %", "Ideal Fail %", "Ideal DNI %")
rownames(ideal_dynamic_sum) <- c("Brake System (DS01)",
                                  "BB Sensor (DF01)",
                                  "Front Brake Disc Noise (DF02)",
                                  "Rear Brake Disc Noise (DF03)",
                                  "Chain Guard Issue (DF04)",
                                  "Wheelset Wobble (DS02)",
                                  "Dynamic E-Shifter Gear Shifting (DF05)",
                                  "Motor (DF06)",
                                  "Kicklock Noise (DF07)",
                                  "Rear Hub Noise (DF08)")
```

```{R Ideal Dynamic Table, include = TRUE, warning = FALSE}
# Make it as a kable
kable(ideal_dynamic_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 6, include = FALSE, warning = FALSE}
# Remove additional variables to save space
rm(DS01_ideal,
   DF01_ideal, 
   DF02_ideal,
   DF03_ideal,
   DF04_ideal,
   DS02_ideal,
   DF05_ideal,
   DF06_ideal,
   DF07_ideal,
   DF08_ideal)
```

```{R Ideal Dynamic Graph Distribution, echo = TRUE, include = FALSE}
# Graph Dynamic Overview
dynamic_3 <- ideal_dynamic %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") + 
    labs(x = "Inspection Item", y = "Percentage Fraction", title = "SA5 DVT Ideal Dynamic QQC Summary")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R Ideal Dynamic Graph Demo}
ggplotly(dynamic_3)
```

## Speedtech DVT OQC Statistics.

This section will summarize data from Speedtech, the following code will illustrate the brief % of pass, fail and did not inspect (DNI)% for both static and dynamic test for DVT bikes.

```{r Speectech Static Data Summary, include = FALSE, warning = FALSE}
# Summarize the data frame
SF01_speedtech <- speedtech_static$Percent[1:3]
SF02_speedtech <- speedtech_static$Percent[4:6]
SF03_speedtech <- speedtech_static$Percent[7:9]
SC01_speedtech <- speedtech_static$Percent[10:12]
SC02_speedtech <- speedtech_static$Percent[13:15]
SF04_speedtech <- speedtech_static$Percent[16:18]
SC02_speedtech <- speedtech_static$Percent[19:21]
SC03_speedtech <- speedtech_static$Percent[22:24]
SS01_speedtech <- speedtech_static$Percent[25:27]
SF05_speedtech <- speedtech_static$Percent[28:30]
SF06_speedtech <- speedtech_static$Percent[31:33]
SF07_speedtech <- speedtech_static$Percent[34:36]
SF08_speedtech <- speedtech_static$Percent[37:39]
SC04_speedtech <- speedtech_static$Percent[40:42]
SC05_speedtech <- speedtech_static$Percent[43:45]
SC06_speedtech <- speedtech_static$Percent[46:48]
SC07_speedtech <- speedtech_static$Percent[49:51]
SC08_speedtech <- speedtech_static$Percent[52:54]
SF09_speedtech <- speedtech_static$Percent[55:57]

speedtech_static_sum <- rbind.data.frame(SF01_speedtech,
                                 SF02_speedtech,
                                 SF03_speedtech,
                                 SC01_speedtech,
                                 SC02_speedtech,
                                 SF04_speedtech,
                                 SC02_speedtech,
                                 SC03_speedtech,
                                 SS01_speedtech,
                                 SF05_speedtech,
                                 SF06_speedtech,
                                 SF07_speedtech,
                                 SF08_speedtech,
                                 SC04_speedtech,
                                 SC05_speedtech,
                                 SC06_speedtech,
                                 SC07_speedtech,
                                 SC08_speedtech,
                                 SF09_speedtech)

colnames(speedtech_static_sum) <- c("Speedtech Pass %", "Speedtech Fail %", "Speedtech DNI %")
rownames(speedtech_static_sum) <- c("Front Light (SF01)",
                                  "Rear Light (SF02)",
                                  "LED Ring (SF03)",
                                  "Frame Noise (SC01)",
                                  "Handlebar Cosmetics (SC02)",
                                  "Kickstand Noise (SF04)",
                                  "E-Shifter Plug Cosmetics (SC02)",
                                  "Charger Plug Cosmetics (SC03)",
                                  "Brake Tube (SS01)",
                                  "Battery Function (SF05)",
                                  "Kicklock Function (SF06)",
                                  "Main ECU (SF07)",
                                  "Horn Function (SF08)",
                                  "Frame Cosmetics (SC04)",
                                  "Front Fork Cosmetics (SC05)",
                                  "Front Fender Cosmetics (SC06)",
                                  "Rear Fender Cosmetics (SC07)",
                                  "Handlebar Grip Gap (SC08)",
                                  "Assistance Level Change (SF09)")
```

```{R Speedtech Static Table, include = TRUE, warning = FALSE}
# Make it as a kable
kable(speedtech_static_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 7, include = FALSE, warning = FALSE}
# Remove additional variables
rm(SF01_speedtech, 
   SF02_speedtech,
   SF03_speedtech,
   SC01_speedtech,
   SC02_speedtech, 
   SF04_speedtech,
   SC02_speedtech,
   SC03_speedtech,
   SS01_speedtech,
   SF05_speedtech,
   SF06_speedtech,
   SF07_speedtech,
   SF08_speedtech,
   SC04_speedtech,
   SC05_speedtech,
   SC06_speedtech,
   SC07_speedtech,
   SC08_speedtech,
   SF09_speedtech)
```

```{R Speedtech Static Graph Setup, echo = TRUE, include = FALSE}
# Graph Static Overview
static_4 <- speedtech_static %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") +
  labs(x = "Inspection Item", y = "Percent Fraction", title = "SA5 DVT Speedtech Static QQC Summary")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R Speedtech Static Graph Demo}
ggplotly(static_4)
```

```{R Speedtech Dynamic Data Summary, include = FALSE, warning = FALSE}
# Summarize the data frame
DS01_speedtech <- speedtech_dynamic$Percent[1:3]
DF01_speedtech <- speedtech_dynamic$Percent[4:6]
DF02_speedtech <- speedtech_dynamic$Percent[7:9]
DF03_speedtech <- speedtech_dynamic$Percent[10:12]
DF04_speedtech <- speedtech_dynamic$Percent[13:15]
DS02_speedtech <- speedtech_dynamic$Percent[16:18]
DF05_speedtech <- speedtech_dynamic$Percent[19:21]
DF06_speedtech <- speedtech_dynamic$Percent[22:24]
DF07_speedtech <- speedtech_dynamic$Percent[25:27]
DF08_speedtech <- speedtech_dynamic$Percent[28:30]

speedtech_dynamic_sum <- rbind.data.frame(DS01_speedtech,
                                 DF01_speedtech,
                                 DF02_speedtech,
                                 DF03_speedtech,
                                 DF04_speedtech,
                                 DS02_speedtech,
                                 DF05_speedtech,
                                 DF06_speedtech,
                                 DF07_speedtech,
                                 DF08_speedtech)

colnames(speedtech_dynamic_sum) <- c("Speedtech Pass %", "Speedtech Fail %", "Speedtech DNI %")
rownames(speedtech_dynamic_sum) <- c("Brake System (DS01)",
                                  "BB Sensor (DF01)",
                                  "Front Brake Disc Noise (DF02)",
                                  "Rear Brake Disc Noise (DF03)",
                                  "Chain Guard Issue (DF04)",
                                  "Wheelset Wobble (DS02)",
                                  "Dynamic E-Shifter Gear Shifting (DF05)",
                                  "Motor (DF06)",
                                  "Kicklock Noise (DF07)",
                                  "Rear Hub Noise (DF08)")
```

```{R Speedtech Dynamic Table, include = TRUE, warning = FALSE}
# Make it as a kable
kable(speedtech_dynamic_sum) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
```

```{R Remove Part 8, include = FALSE, warning = FALSE}
# Remove additional variables to save space
rm(DS01_speedtech,
   DF01_speedtech, 
   DF02_speedtech,
   DF03_speedtech,
   DF04_speedtech,
   DS02_speedtech,
   DF05_speedtech,
   DF06_speedtech,
   DF07_speedtech,
   DF08_speedtech)
```

```{R Speedtech Dynamic Graph Distribution, echo = TRUE, include = FALSE}
# Graph Dynamic Overview
dynamic_4 <- speedtech_dynamic %>%
  ggplot(aes(x = Pseudo_Code, y = Qty, fill = Result)) +
  geom_bar(position = "fill",stat = "identity") + 
    labs(x = "Inspection Item", y = "Percentage Fraction", title = "SA5 DVT Speedtech Dynamic QQC Summary")+
  theme(axis.text.x = element_text(angle = 40, hjust = 1, size = 10),
        axis.text.y = element_text(size = 10),
        axis.title = element_text(size = 11),
        plot.title = element_text(hjust = 0.5, size = 16),
        legend.title = element_text(size = 8),
        legend.text = element_text(size = 8))+
  scale_fill_manual(values = c("#FAFF8C","#FA0947","#09DE87"))
```

```{R Speedtech Dynamic Graph Demo}
ggplotly(dynamic_4)
```

```{R Remove part 9, include = FALSE}
rm(oqc_ideal, oqc_overall, oqc_speedtech, oqc_tconn, overall_dynamic, overall_static, tconn_dynamic, tconn_static, speedtech_dynamic, speedtech_static, ideal_dynamic, ideal_static)
```
## Conclusion

Based on the observation and required criteria, the first past yield for PQE is to consider a *passed* bike is a bike which passes ALL the inspection items without rework done or being concessioned.

After observing all the DVT bikes, the yield rate for PQE's observation is 0% due to all of the DVT bikes require rework process or concession. Reasons such as e-shifter stuck at gear 3 during test ride and other concession items from brake malfunction or kickstand hitting frames shall be considered for significant improvement before going to PVT or even mass production.

Due to the instability within the component of SA5 Bike, PQE does not recommend to proceed PVT unless these open findings from DVT is solved or improvised.