Bo-Yen shen portfolo 2

PORTFOLIO Bo-Yen Shen

沈柏硯 成功大學工業設計系 105 級 專長 : 模型 造型 材料 工作室地縛靈 缺工具 沒材料 機器不會用 找他就對了 還有很多未知的領域要探索 還有很多進步的空間 換言之 還有無限的可能性

經歷 台南一中 101 級國樂社美宣 成大國樂社打擊分部長 南友之夜美宣組員 工設系期末聯展負責人 ( 基本設 計B班) 工設周校園布置組組員 成大國樂 2014 巡迴演出美宣

product design 4

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b am m w. ww

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店 書 蔓步 e

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oo .co m

台 南 市 東區

裕和

路2

61號

店 步書 3蔓 183 (06)331332 2/(09)7572

s ht Rig All

rv se Re

蔓步書店

www.mamboo.com 台南市東區裕和路261號 (06)3313322/(09)75721833 frank2626267@gmail.com 沈柏硯/倉儲管理 To:

image design 36

Statistic Methodology 48

product design

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product design

Product design projet 1 shape of brush 5

product design

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product design

20 張發想草圖 ------ 烤肉刷 水平思考 把所有的可能性紀錄在紙上 一開始先觀察燒烤店的烤肉刷使用情形 發現有一項很重要的特點 水 清潔時需要用水來軟化卡讚網子上的肉屑 並且沖洗乾淨 如果烤肉刷能加上注水這項功能 那麼或許能讓刷子的使用上更為方便 7

product design

20 張發想草圖 ------ 烤肉刷 垂直發想 深入思考 確定了主要的幾個大方向 可以裝水 更換刷毛或是布 還有伸縮刷頭的概念 探索更好握的造型 角度是否符合人體工學 方向 弧度 刷面 面面俱到 8

product design

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product design

草模 經過了 20 張垂直發想的草圖後 決定以 [ 含水的刷子 ] [ 伸縮的刷子 ] 兩種造型來做草模 草模可以表現的東西遠大於 sketch 做出來後發現各有優缺 經過審慎的思考後 認為含水的刷子是一種嶄新的概念 可以繼續思考並且做出精模 10

product design

握把 設計較長

可以雙手持握

特色 具有可以讓水流出來的接縫

拆開後的內部構造

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product design

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product design

後方注水孔

前方水量調整紐

確定了產品的明確方向後 開始改良造型與外觀 首先把直的握把改成傾斜角度以符合人體工學 更改了注水孔的設計 換成把水存放在刷子裡 以免烤肉附近沒有水管可以接 一開始的想法是用旋鈕控制出水量 後方則是注水孔 但是在刷頭卻設計太小 而且注水孔的角度會卡到手腕 因此有必要重新思考更精細的部分 13

product design

最後的產品精模 注水孔改成在刷子的正上方 加長的握把可以雙手持握 產品名稱 :SBRUSH 烤肉刷 針對族群 : 國外大型式戶外烤盤 特點 : 刷身可以裝水 , 在清理時增加清潔力 造型概念 : 由於烤肉刷需要相當大的力氣刷洗 , 所以把握 把與刷身改成能讓手腕垂直施力的角度 , 減少人因上的 extention, 加長過的握把可以雙手持握 , 更能有效施力

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product design

I have water in my body 15

product design

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product design

Product design projet 2 Biomimetic brush 17

product design

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product design

20 張發想草圖 ------ 仿生設計 一樣先水平思考 各種動物擁有不同的特點 向動物學習 以大自然為師 從中發展出不同的造型 進而讓產品擁有自己的生命 在這之中選擇了射水魚 海龍 三角龍以及貓伸懶腰 作為之後垂直發展的要素 19

product design

20 張發想草圖 ------ 仿生設計 仿生事實上還有分許多種 動作 形狀 意象 結構 材質 功能 ............... 各種不同的詮釋 但是如果模仿得太像又會失去深度 反而看起來像是玩具 其中的分寸拿捏需要好好斟酌 最後選擇了動作仿生 貓咪伸懶腰 20

product design

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product design

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product design

製作過程 要在烤肉刷中融入貓咪伸懶腰的意象 並沒有想像中那麼簡單 必須要兼顧功能性以及伸懶腰的感覺 為此 我畫了好幾十張的 sketch 從中尋找最有感覺的造型

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product design

最後的產品精模 產品名稱 :CBRUSH 烤肉刷 針對族群 : 國內小型家庭式烤網 特點 : 刷身造型取自貓咪伸懶腰的意象 , 彎曲 的身形可以適合各種角度 , 也可懸掛在任何地 方 在下方刷毛處加裝了鐵片 , 可以去除較難清洗 或是卡在網上的焦屑

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product design

a brush in the shape of cat stretching

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product design

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product design

Product design projet 3 Humor design 27

product design

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product design

20 張發想草圖 ------ 幽默設計 第一次有畫不出來的狀況 要幽默又要有功能性 這兩者感覺上是無法兼容並存的 要在這兩者間找出交集 會心一笑 讓使用者快樂

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product design

20 張發想草圖 ------ 幽默設計 一樣地 , 幽默也是有許多種設計的方法 重複 卡通化 動作 表裡不一 錯覺 移花接木 並置 誇大 .......... 各種方法都有不同的表現 這次垂直選了齒輪 墨水筆 小便斗作為造型研究 最後選擇壁掛式的齒輪來發展

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product design

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product design

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product design

內部構造 我希望可以用轉的來擠出沐浴乳 所以內部的機構需要製作的十分精細 因此這次花的許多時間在思考內部的連動裝置 最後應用了機槍的排彈裝置 讓齒輪每轉一圈底下的開口就會打開一次 再稍微改造一下讓中間可以按壓 如此一來就有按跟轉兩種開啟方式

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product design

最終的產品精模 產品名稱 :ROLL&TURN 沐浴乳 / 洗髮乳罐 幽默設計 : 利用不可能出現在浴室裡的東西 --- 齒輪 營造出一種反差的效果 產品說明 : 把齒輪撥轉會帶動中間的機構 , 打開下面的孔 , 中間轉 軸也是按鈕 , 按下去會連動到中間的機構 , 讓原本被擋住的孔露 出來 , 沐浴乳自然就流出來了 , 當使用時看到齒輪一起轉動 , 幽默 感便勾起了嘴角的微笑 幽默特性 : 重複 + 反差

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product design

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imagedesign design product

蔓步書店

www.mamboo.com 台南市東區裕和路261號 (06)3313322/(09)75721833 frank2626267@gmail.com 沈柏硯/倉儲管理

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image design product design

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b am m w. ww

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店 書 蔓步 ve

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台 南 市 東區

裕和

路2 6

店 步書 3蔓 1號 (0 2183 6)331332 2/(09)757

r se Re ts h g Ri All

To:

Image design project 1 CIS design 37

imagedesign design product

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CIS---------company identify system 品牌名稱 : 蔓步書店 mambookstore 設計理念 : 以腳印作為步入生活的意象 蜿蜒的藤蔓將藝術送至每個人的心中

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image design product design

第一版 第二版 單純地將店名與 logo 擺在一起 加上書本意象 但是兩者關連性並未顯現 但是效果依然不明顯

最終版 將字形做了變化 再加上商店的特色 最終的 logo 終於產生

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imagedesign design product

CD 包裝設計

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Re se rv ed

w w /w s:/ tp ht

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店 書 蔓步 .m am bo o.c om

店 步書 台南 3蔓 3 8 市東 1 572 區裕 (09)7 和路2 61號 (06) 3313322/

s ht ig lR l A

image design product design

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b am m w. ww

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店 書 蔓步 e

d

oo .co m

台 南 市 東區

裕和

路2

61號

3 183 (06)331332 2/(09)7572

書店 蔓步

s ht Rig All

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蔓步書店

www.mamboo.com 台南市東區裕和路261號 (06)3313322/(09)75721833 frank2626267@gmail.com 沈柏硯/倉儲管理 To:

最終 LOGO 與 CIS 展版

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imagedesign design product

? e ss m

a p r u su

o y e Dar

e g n e l l a a r h r c a c

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image design product design

f l rs

u o y e g n i c a

Image design project 2 poster making 43

imagedesign design product

海報製作 ------- 大聲公比賽 / 賽車比賽 運用了基本 photoshop 的功能 遮色片 模糊濾鏡 特殊效果 以及文字在海報中的編排位置

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image design product design

海報製作 ------- 國樂社期末成發宣傳海報 運用了特殊效果筆刷 分析過色彩計畫後選擇了暖色調來呈現國樂 希望能帶出溫馨歡樂的感覺

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imagedesign design product

產品名稱:SBRUSH烤肉刷 造型概念:由於烤肉刷需要相當大的力氣刷洗,所以把握把與 刷身改成能讓手腕垂直施力的角度,減少人因上的extention, 加長過的握把可以雙手持握,更能有效施力 特點:將刷身設計成可以裝水,如此在清洗烤肉架時水便可將 刷下的碎屑帶走,讓清潔效果倍增

沈柏硯 模型機構狂熱者 工作室亂源 三日不食補土味 便覺面目可憎 以一種過度燃燒生命的方式 認真過著每一天。

I have water in my body

產品名稱:CBRUSH烤肉刷 仿生概念:從貓咪伸懶腰的動作發想而來 使用:彎曲的握把可以符合各種拿法,有效減少手腕的受力 前端的鐵片可以除去卡在烤肉架上的焦屑 方便且省力的造型,讓烤肉跟貓咪伸懶腰一樣 姿態優雅卻不失氣質 仿生方法:動作+色彩

a brush in the shape of cat stretching Project

Designer

Student number

University

E-mail

SBRUSH/CBRUSH

沈柏硯 Bo-Yen Shen

F34011231

National Cheng Kung University Tainan city, Taiwan Department of Industrial Design

frank2626267@gmail.com

期末聯展產設展板設計

產品名稱:ROLL&TURN沐浴乳瓶 幽默設計:利用不可能出現在浴室裡的東西---齒輪 營造出一種反差的效果 產品說明:把齒輪撥轉會帶動中間的機構,打開下面的孔中間轉軸 也是按鈕,按下去會連動到中間的機構,讓原本被擋住的孔露出來, 沐浴乳自然就流出來了,當使用時看到齒輪一起轉動,幽默感便勾 起了嘴角的微笑 幽默特性:重複+反差

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Project

Designer

Student number

University

E-mail

ROLL&TURN

沈柏硯 Bo-Yen Shen

F34011231

National Cheng Kung University Tainan city, Taiwan Department of Industrial Design

frank2626267@gmail.com

image design product design

sketch 展本封面編排

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statistic methodology

Assignment/Study 1: Design Implications with Frequency Distributions Industrial Design 105 沈柏硯 F34011231 杜孟霖 F34011150 呂秉融 F34011257

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statistic methodology

↑Design sketch of the bag for female students.

↑The prototype for the design sketch above.

The main color, black, ďŹ ts the results we found in the histograms and the tables.

And it can also hold the things-personal items, books, stationery items-female students usually have in their bags.

Because most of the female students bring their personal items, we design a bigger front bag for the backpack.

Statistic Methodology work1 bage design

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statistic methodology Description: 1. The shape of the distribution:negatively skewed.

2. Girls prefer longer bags, maybe that’s because it can contain more things.

3. But the numbers of the height concentrate between 41-45 cm, not the bigger the better.

Purpose

The purpose of this assignment is to provide us with opportunities to create frequency distributions and understand how the procedures can be used in the real world to inform product designs.

Methodology

Procedures: Using excel to analyze the data, we can find out frequency distributions.

Population: All the students in the class, 54 people, 24 male, and 30 female.

Equipment: Microsoft Excel and Word

Relative Frequency Distribution for“Height of Bag “ (Male)

8 7

Results: (1) The types of data (Qualitative, Quantitative, or Ranked)

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The type of data Quantitative Qualitative Qualitative Quantitative Quantitative Qualitative Qualitative

5

QUANTITY

Data Purchase time (year) Color Design Height (cm) Volume (cm3) Gender (Bag owner) Types of items in bag

4 3 2 1

(2) The relative frequency distribution for “Height of bag”

0

Relative Frequency Distribution for“Height of Bag“ (Female)

16-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60

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HEIGHT (CM) 10

Class interval 16-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60

QUANTITY

8 6 4 2 0 21-25

Class interval 21-25 26-30 31-35 36-40 41-45 46-50

26-30

31-35

36-40

HEIGHT (CM)

Frequency 1 5 2 9 10 3 30

41-45

46-50

Relative Frequency Distribution for“Height of Bag “ 16 14 12

QUANTITY

10 8 6 4 2 0 16-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60

HEIGHT (CM)

Frequency 1 2 7 3 10 15 10 5 1 54

Relative Frequency 0.019 0.037 0.129 0.055 0.185 0.277 0.185 0.092 0.019 1

Description: 1. The shape of the distribution: normal but with some outliners.

2. Depend on the diagram, we can see that the students often use bags of the height of 41-45 cm.

3. Some students use bags of the height of 26-30 cm, we think that the height is appropriate for girl’s small bags.

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Relative Frequency 0.042 0.042 0.083 0.042 0.042 0.208 0.291 0.208 0.042 1

Description: 1. The shape of the distribution: skewed.

2. The number of the height concentrate between 41-55, the range is bigger than girls’, and the average height is larger than girls’.

3. But there are still some small bags, we assume that the small ones are only for casual using.

Relative Frequency 0.033 0.167 0.067 0.300 0.333 0.100 1

Class interval 16-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60

Frequency 1 1 2 1 1 5 7 5 1 24

statistic methodology Relative Frequency Distribution for “Volume of Bag“ (Male)

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5

QUANTITY

4

3

2

1

0

VOLUME (CM3)

Class interval 1-5000 5001-10000 10001-15000 15001-20000 20001-25000 25001-30000 30001-35000 35001-40000 40001-45000 45001-50000 50001-55000 55001-60000

Frequency 2 1 2 3 5 1 5 1 2 0 1 1 24

Relative Frequency 0.083 0.042 0.083 0.125 0.208 0.042 0.208 0.042 0.083 0.000 0.042 0.042 1

Description: 1. Depend on the chart , we can see that the sizes of the boys’ bags don’t have a normal pattern.

2. But, we still can compare two chart and see that the average size of the boys is much bigger than girls’

Relative Frequency Distribution for “Volume of Bag“

(3) The relative frequency distribution for “Volume of bag”

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Relative Frequency Distribution for “Volume of Bag“ (Female)

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14 12

10

8

8

QUANTITY

QUANTITY

10

6 4

6

4

2 2

0 0 VOLUME (CM3) VOLUME (CM3)

Class interval 1-5000 5001-10000 10001-15000 15001-20000 20001-25000 25001-30000 30001-35000 35001-40000 40001-45000 45001-50000 50001-55000 55001-60000

Frequency 3 4 7 10 15 2 5 1 2 1 1 1 54

Relative Frequency 0.056 0.074 0.130 0.185 0.278 0.037 0.093 0.019 0.037 0.019 0.019 0.019 1

Description: 1. The shape of the distribution: positively skewed.

2. Depend on three charts above, we can see that sometimes small group may not follow the rules, but big group can still follow the rules.

Class interval 1-5000 5001-10000 10001-15000 15001-20000 20001-25000 25001-30000 30001-35000 35001-40000 40001-45000 45001-50000

Frequency 1 3 7 7 10 1 0 0 0 1 30

Relative Frequency 0.033 0.100 0.233 0.233 0.330 0.033 0.000 0.000 0.000 0.033 1

Description: 1. The shape of the distribution: positively skewed.

2. We assumed the reason which makes the shape is skewed is because we often like bigger bags for which can be put much more things than small ones, but the size can’t be too large to carry.

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statistic methodology (4) The frequency distribution for “Bag design” Frequency Distribution for “Bag Design”(Female) 25

Frequency Distribution for “Bag Design”

45 40

20

30 QUANTITY

QUANTITY

35 15

10

5

25 20 15 10

5 0 Backpack

Messenger Bag

Tote Bag

0

Other

Backpack

BAG DESIGN

Description: 1. Depend on the diagram, we can see girls prefer backpack than any other kinds of bags.

2. We assume that’s because backpacks are in trend now.

Messenger Bag

Tote Bag

Other

BAG DESIGN

Description: 1. We can see that the most students like backpacks .

(5)The frequency polygon(with Year on the x-axis) for “Bag Design” Frequency Distribution for “Bag Design”(Male)

Bag Design

20

18

14

16

12

QUANTITY

14

10

12

8

10

6

8 6

4

4

2

2 0

0 Backpack

Messenger Bag

2006

Other

2007

2008

2009

2010

2011

2012

2013

YEAR

BAG DESIGN

Backpack

Description: 1. Depend on the diagram, boys also prefer backpacks.

Messenger Bag

Tote Bag

Other

Description: 1. We found that the most backpacks are bought after 2010, we guess that the trend of carrying backpacks is flowering after 2010.

2. The backpacks are the most favorite option among the teens.

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Frequency Distribution for “Types of Items in Bag”

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(6) The frequency polygon distribution for “Types of Items in Bag” 35 30

30 20 10

25

Quantity

40 Quantity

Frequency Distribution for “Types of Items in Bag” (Female)

0

20 15

Personal Items

Book

Stationery Items

Food/Drink

Small/Portable E-device

Notebook/ Tablet PC

Others

Types of Items in Bag

10 5 0 Personal Items

Book

Stationery

Food/Drink

Items

Small/Portable

Notebook/

E-device

Tablet PC

Others

Description: 1. Most students carry their personel items, but the definition of “ personal item ” is too unclear to know the sizes of the items, we can’t design our bag only by one type.

2. We found that many students carry books and some of them carry laptops, so the size of the bag must be big enough to carry the large things.

(7) The relative frequency distribution for “Color of bag”

Types of Items in Bag

Description: 1. Most girls carry their personel items, but the definition of “ personal item ” is too unclear to know the sizes of the items, we can’t design our bag only by one type.

2. We found that many girls carry books and some of them carry laptops, so the size of the bag must be big enough to carry the large things.

Frequency Distribution for “Types of Items in Bag” (Male) 20 18 16

Quantity

14 12 10 8 6 4 2 0

Personal Items

Book

Stationery Items

Food/Drink

Small/Portable E-device

Notebook/ Tablet PC

Others

Types of Items in Bag

Description: 1. Most boys carry their personel items, but the definition of “ personal item ” is too unclear to know the sizes of the items, we can’t design our bag only by one type.

2. We found that many boys carry books and some of them carry laptops, so the size of the bag must be big enough to carry the large things.

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Description: 1. Girls have more choice on the colors of the bag.

2. We found that most of the boys use black as the color of their bags.

3. Most of the students in the ID statistic class choose black as their favorite.

statistic methodology

Design/Rationale

Based on the information you obtained from the above, we provide the bag design guidelines for the male and female students in the ID statistics class.

For female students, (1) The height of the bag might be between 41-45 cm.

(2) The volume of the bag might be between 20001-25000 cm3.

(3) The bag design might be backpack.

(4) The bag could hold personal items, books, and stationery items Bags fit in with the guidelines might easily catch female students’ eyes.

For female students, (1) The height of the bag might be between 46-50 cm.

(2) The volume of the bag might be between 20001-25000 cm3 or between 30001-35000 cm3.

(3) The bag design might be backpack.

(4) The bag could hold personal items, notebook/tablet PC, and stationery items Bags fit in with the guidelines might easily catch male students’ eyes.

↑This is the look of our bag design.

↑Design sketch of the bag for female students.

↑The prototype for the design sketch above.

The main color, black, fits the results we found in the histograms and the tables.

And it can also hold the things-personal items, books, stationery items-female students usually have in their bags.

Because most of the female students bring their personal items, we design a bigger front bag for the backpack.

↑Design sketch of the bag for male students.

↑The prototype for the design sketch above.

The main color, black, fits the results found in the histograms and the tables of male students in the ID statistic class.

It can also hold the things-personal items, notebook/tablet PC, stationery items-male students usually carry in their backpacks There is a layer designed for carrying the notebook and tablet PC because most of the male students carry their notebooks/tablet PCs in their bags.

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statistic methodology

Assignment/Study 2: Normal Distribution and Z Scores Industrial Design 105 沈柏硯 F34011231 杜孟霖 F34011150 呂秉融 F34011257

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statistic methodology

FP

10 FP FP

Then we design the chair, the height of the whole chair is 76 cm. And the height from the seating position to the floor is the perfect height for 5 th percentile female to seat, 38.6 cm. (The perfect height for 5th percentile female to seat has mentioned in the third part of the result.) From the picture, we can see a white cylindrical part with a controller. Considering the population out of the range from 95th percentile male to 5th percentile female, we extend the adjustable part-the white part-into 10 cm. The newly designed chair can fit almost 99% user by adjusting the height. Besides, the chair has wheels make it easily to move and the seat is rotatable.

Statistic Methodology work2 Table/Chair design

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statistic methodology Purpose

The purpose of this activity is to provide the class with the experience of using anthropometric data and z scores to design safe workstations.

Introduction

Anthropometry is study of human body dimensions and other physical characteristics of the body such as volume, centers of mass, inertial properties, and masses of body segments. Static anthropometric dimensions are measurements taken when the body is in a fixed position. Three seated measurements will be made of every class member and percentiles will be calculated for males and females.  Popliteal height: Popliteal Height defines the correct seat height. The measurement is taken from the floor to the back of the knee when seated, with thighs horizontal and lower leg vertical with feet flat to the floor. 

Elbow resting height: Elbow resting height is the vertical distance from the sitting surface to the bottom of the elbow.



Compressed seat height: Compressed seat height is the vertical distance from the floor to the sitting surface.

Results

1. Find the dimensions measured of the 5th percentile female and the 95th percentile male.

First, we can calculate the mean and standard deviation for males and females by using the function the in Microsoft Excel. Then we can use the equation of Z Scores to calculating the value of the popliteal height. We check the table of normal distribution and Z Scores in the textbook to get the Z Scores of the 5th percentile female and the 95th percentile male.

X−μ , so the X = μ + z ∗ σ.

The equation of Z Score is Z = σ (In this equation, Z is the Z score, X is the value of the popliteal or elbow resting height of male/female, μ is the mean of popliteal or elbow resting height of male/female and σ is the standard deviation of the popliteal or elbow resting height.)

Female’s popliteal height: (1) The mean of female’s popliteal height: 40.47 cm (2) The standard deviation of female’s popliteal height: 3.10 cm The 5th percentile female’s Z score is -1.64.

X=μ+ z*σ=40.7- 1.64* 3.10= 35.616 The 5th percentile female’s popliteal height is about 35.62 cm.

Female’s elbow resting height: (1) The mean of female’s Elbow resting height: 23.47 cm (2) The standard deviation of female’s elbow resting height: 3.03 cm X =μ+ z*σ=23.7- 1.64* 3.03= 18.7308 The 5th percentile female’s elbow resting height is about 18.73 cm.

Male’s popliteal height: (1) The mean of male’s popliteal height: 42.30 cm (2) The standard deviation of male’s popliteal height: 3.56 cm The 95th percentile male’s z-score is 1.65.

X=μ+ z*σ=42.30+ 1.65* 3.56= 48.174 The 95th percentile male’s popliteal height is about 48.17 cm.

Methodology

Procedures: Using excel to analyze the data, we can calculate all we need.

Population: All the students in the class, 54 people, 24 male, and 30 female.

Equipment: Ruler, sheet, any rectangular object for the measurement.

Microsoft Excel, Word and the textbook for data analysis.

2. Determine the Z score and the percentile that corresponds to the popliteal height of each of your group members. (By using the equation of Z Scores and checking the table of normal distribution and Z Scores in the back of the textbook.)

The equation of Z score:

Z=

X−μ

σ (In this equation, Z is the Z score, X is the value of the popliteal or elbow resting height of male/female, μ is the mean of popliteal or elbow resting height of male/female and σ is the standard deviation of the popliteal or elbow resting height.)

(1) 杜孟霖 ( popliteal height: 48.5 cm) Z score of him: (48.5-42.3)/ 3.56 = 1.74, correspond to 0.4591 50+45.91=95.91 The percentile of him: 95.91% (2) 沈柏硯 ( popliteal height: 47.4 cm) Z score of him: (47.4-42.3)/ 3.56 = 1.43, correspond to 0.4236 50+42.36=92.36 The percentile of him: 92.36%

Male’s elbow resting height: (1) The mean of male’s Elbow resting height: 25.52 cm (2) The standard deviation of male’s elbow resting height: 3.97 cm X=μ+ z*σ=25.52+ 1.65* 3.97= 32.0705 The 95th percentile male’s Elbow resting height is about 32.07 cm

4. Determine the height if we were to design a table for the 5th percentile female and see if the classroom tables accommodate these female students.

The height is actually popliteal height plus elbow resting height of the 5 th percentile female.

So, 35.62+ 18.73= 54.35 cm The height of the classroom tables is 71 cm and the height of the newly designed table for the 5th percentile female student is 54.35 cm. Apparently, the classroom tables don’t accommodate these female students.

5. Discuss what happens to the legs of a female student who is below the 5th percentile when seated in the newly designed chair and the legs of the male student who is above the 95th percentile. Then find out what could be done to remedy the problems, we illustrate our idea with some sketches.

The legs of female students who is below the 5th percentile can’t touch the floor. For the male students who is above 95th percentile, his thighs and lower leg can’t be perpendicular, because his legs are too long. We have some idea sketches in the following, and it will show you how we solve the problems.

(3) 呂秉融 ( popliteal height: 45.2 cm) Z score of him: (45.2-42.3)/ 3.56 = 0.82, correspond to 0.2936 50+29.36=79.36 The percentile of him: 79.36%

3. Determine the range of height adjustment if we were designing an office chair to accommodate the 5th percentile female and 95th percentile male students so that their feet touched the floor when seated.

In this section, we also need to consider the height of the heels which is about 3 cm. So, the perfect height for the 5th percentile female to seat on the chair is the female’s popliteal height plus the height of the heels. And the range of height adjustment is from the male’s popliteal height to the perfect height for the 5th percentile female to seat on the chair. It means that the height we want is determined by the male’s popliteal height cutting the perfect height for the 5th percentile female to seat on the chair.

35.62+ 3= 38.62 cm 48.17- 38.62= 9.55 cm The range of height adjustment is from 38.62 to 48.17 cm.

The height of adjustment will be 9.55 cm.

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↑ This is a full-look of our design.

statistic methodology

We first design a table for all the students at a height of 71 cm, the original height of the classroom table. We can see that there are two round holes on the table. It is design for the people who use the notebook-PC can put their charger neat on the table. The table has a sunken part that can put the notebook-PC there.

It is tilt and can make the user more comfortable when using the notebook-PC. On the left side of table have two hangers for the user to hang things like rag.

There is also space for user to put their bags in.

FP

10 FP FP

Then we design the chair, the height of the whole chair is 76 cm. And the height from the seating position to the floor is the perfect height for 5 th percentile female to seat, 38.6 cm. (The perfect height for 5th percentile female to seat has mentioned in the third part of the result.) From the picture, we can see a white cylindrical part with a controller. Considering the population out of the range from 95th percentile male to 5th percentile female, we extend the adjustable part-the white part-into 10 cm. The newly designed chair can fit almost 99% user by adjusting the height. Besides, the chair has wheels make it easily to move and the seat is rotatable.

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statistic methodology

Assignment 3: Ergonomics mouse design with correlation analysis

Industrial Design 105 呂秉融 F34011257

杜孟霖 F34011150 沈柏硯 F34011231

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statistic methodology

Then we show the photo putting two models together.

Conclusion

After all the analyses we have made, we found out that the mice students using are not so correlated to their own hands. We assume the reason is because most of the students’ mice are bonus when they buy computers. Since the mouse is free, the owner would not be so hypercritical on it, no matter the mouse is fit or not. From all the works, we got to know how correlation analyses could be used to identify the size of your own products that will work best for your customers.

If we use the statistics methods into our process of making new products, we can prevent making things which are useless or out of fashion.

Statistic Methodology work3 mouse design

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statistic methodology Purpose

The purpose of this exercise is to introduce how correlation analysis could be used to identify the size of ergonomic mouse that will work best for your customers.

Introduction

Correlational research is to discover relationships between two or more variables.

Relationship means that an individual’s status on one variable tends to reflect his/her status on the other. Correlation does not imply causation. However, it helps us understand related variables, conditions, and behaviors. In user experience, a correlation matrix is often used to show all pair-wise correlation information in one place. Such information provides important insight for design guidelines.

In this exercise, we are going to find out the relationship between hand and mouse.

Methodology

Procedures: Using IBM SPSS to analyze the data.

Population: All the students in the class, 53 people, 24 male, and 29 female.

Equipment: ruler, IBM SPSS, Microsoft Excel and Word.

Results

1. Show a frequency polygon of “color” that separated into 2 bars, one representing the male owners and the other one for the female owners.

20 18

Quantity

16 14 12 10 8 6

female male

4 2 0

Black

Blue

Gold

Grey

Pink

Main color

Red

Silver

White

Figure 1 Frequency Polygon of main color From the figure 1, we can see that most of the male and female students have black mice. Besides, white is the second most color that male and female students choose as their mice’s color.

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statistic methodology

2. Show the scatter plots for the following paired variables and performing correlation analysis for the paired variables. (1) Hand length v.s. mouse length (2) Hand length v.s. mouse height (3) Hand breadth v.s. mouse width

Table 2.3 Mean, standard deviation and quantity of hand length and mouse height Table 2.1 Mean, standard deviation and quantity of hand length and mouse length

Table 2.4 Correlation analysis for ”hand length v.s. mouse height” from SPSS Table 2.2 Correlation analysis for ”hand length v.s. mouse length” from SPSS From table 2.2 and figure 2.1, we can see that the hand length and the mouse length would be lowly correlated according to the Pearson product-moment correlation coefficient at 0.05 level of significance in a two-tailed test.

From table 2.4 and figure 2.2 above, we can see that the hand length and the mouse height would be lowly positive correlated according to the Pearson productmoment correlation coefficient without enough significance.

Table 2.5 Mean, standard deviation and quantity of hand breadth and mouse width

Table 2.6 Correlation analysis for ”hand breadth v.s. mouse width” from SPSS From table 2.6 and figure 2.3 above, we can see that the hand breadth and the mouse width would be lowly positive correlated according to the Pearson productmoment correlation coefficient without enough significance.

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statistic methodology 3. Rank the data for “Hand length,” “Hand breath,” “Mouse length,” “Mouse height” and “Mouse width” and perform the same three correlation analysis in Question #2 with SPSS.

After ranking the data, we use Spearman's rank correlation coefficient for the correlation analysis.

Compare with the same three correlation analyses using Pearson productmoment correlation coefficient in Question#2, we can found that there are differences between the two same analyses using two kinds of correlation coefficient. In the analysis for "hand length v.s. mouse length" in Question#2, we realized that they have a low-positive correlation at a 0.05 level of significance in a two-tailed test (table 2.2). However, the two variables have low-positive correlation without enough significance in the two-tailed test in Question#3 (table 3.1).

Yet the results of analyses are totally different when speaking about the other two paired variables.

Table 3.1 Correlation analysis for ”hand length v.s. mouse length” from SPSS

We are lack of significance to say the variables-hand length and mouse heightare lowly and positively correlated in the correlation analysis using Pearson correlation coefficient in Question#2 (table 2.4) but we have 0.05 level of significance to say the variables are lowly and positively correlated in the correlation analysis using Spearman's rank correlation coefficient in Question#3 (table 3.2). The situation of the last paired variables, hand breadth and mouse width, is same as the situation of hand length and mouse height. The result of the last pair of variables shows none-significance in Question#2 (table 2.6) but a 0.05 level of significance in Question#3 (table 3.3).

Table 3.2 Correlation analysis for ”hand length v.s. mouse height” from SPSS

4. Perform correlation analysis for the “gender,” “color,” “price,” “design” and “body symmetry.”

In this part, we use product-moment correlation coefficient as the type of the correlation coefficient. Before performing the correlation analysis, we first change

Table 3.3 Correlation analysis for ”hand breadth v.s. mouse width” from SPSS

the variables in to numbers in the following: ◎ Gender (male=1 and female=2) ◎ Color (Black=1 and Non-black=2) ◎ Price (low=1 and high=2) ◎ Design (wired=1 and wireless=2) ◎ Body Symmetry (Symmetric=1, Asymmetric=2) Then we start running the correlation analysis matrix for the variables in the SPSS. Table 4.1 and 4.2 are the results we get from SPSS.

5. The correlation analysis for “gender v.s. mouse length.”

Table 5.1 Mean, standard deviation and quantity of gender and mouse length

Table 4.1 Mean, standard deviation and quantity of gender, main color, price, design and body symmetry

Table 5.2 Correlation analysis for ”gender v.s. length” from SPSS In Question#5, we use Pearson product-moment correlation coefficient for the correlation analysis. From table 5.2, we can see that the gender and the mouse length would be lowly negative correlated according to the Pearson productmoment correlation coefficient at 0.01 level of significance in a two-tailed test.

The Pearson product-moment correlation coefficient is minus because we assume the male is 1 and the female is 2, causing the mouse length is longer when the gender is small and making it minus.

Design/Rationale Table 4.2 Correlation analysis for gender, main color, price, design and body symmetry From table 4.2, we can see that the price is highly positive correlated with the design of the mouse according to the Pearson product-moment correlation coefficient at 0.01 level of significance. So, when the design is better, the price is higher. We can also see that the main color is lowly positive correlated with the design of the mouse and the price according to the Pearson product-moment correlation coefficient at 0.05 level of significance.

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After doing the five question, we realized that mice students using are lowly correlated to their hands. And the most correlated paired variables are design and price which means when the design is better, the price is higher.

As we noticed all these information, we decided to take the mean of the variables of the mouse as the size of our designed mouse for both male and female students. We round the means to the nearest whole number. The mouse length is 10cm showed in table 2.1, the mouse height is 3cm showed in table 2.3, and the mouse width is 6cm showed in table 2.5.

And, for the color, we choose the most used color that we get from the frequency polygon in Question#1 (figure 1), black, as the main color of the mice, using grey as the secondary color of the designed mice.

Then we are going to show the sketches and model picture of our designed mice for male and female students.

For the shape, the upper one is designed for male students and the lower one is for female students in the sketches and the model pictures below. The designed mouse for male students use hard ridges in the designed and the one for female students uses soft lines.

statistic methodology

Then we show the photo putting two models together.

Conclusion

After all the analyses we have made, we found out that the mice students using are not so correlated to their own hands. We assume the reason is because most of the students’ mice are bonus when they buy computers. Since the mouse is free, the owner would not be so hypercritical on it, no matter the mouse is fit or not. From all the works, we got to know how correlation analyses could be used to identify the size of your own products that will work best for your customers.

If we use the statistics methods into our process of making new products, we can prevent making things which are useless or out of fashion.

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Bo-Yen Shen frank2626267@gmail.com 0975721833