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산업공학39

Process Capability Analysis * Process Capability Analysis : 제조 공정을 안정 상태로 유지한 경우 그 공정이 만들어내는 품질의 달성 능력을 말한다. [네이버 지식백과] 공정 능력 [process capability, 工程能力, こうていのうりょく] (용어해설) - Cp, Cpk, Cpkm - C.I and Hypothesis testing for Cp * Process Capability Ration : Cp = distance between specification limits / 6*sigma - 프로세스가 양측 규격인 경우 적용 - Cp = 1 means the process are uses up 100% tolerance band with 0.27% (2700ppm) nonconforming units.. 2024. 3. 26.
Cost-benefit Analysis (비용편익분석) * Cost - benefit analysis (비용편익분석) - estimate the strengths and weakness of alternatives that satisfy transcations, activities or functional requirement for the business 투자재원의 한계 내에서 어떤 사업을 선택하는것이 바람직한 것인지 분석 - benefits : labor, time and cost-savings - purpose: 1) to determine if it is a sound sound investment/ decision (justification/ feasibility) 2) to provide basis for comparing benefits and .. 2024. 3. 26.
X bar and S Control Chart S chart 는 언제 쓰면 될까 ? 1) Sample size 'n > 10' 일 때 ( n이 10보다 작거나 같을 경우 R 차트를 사용하는것이 좋다) 2) Used for variable sample size => Subgroups have different sample size 1. X bar and S control chart with variable sample size (subgroup의 sample size가 다를 경우) m : # of samples/ subgroups ni : sample size for each samples/ subgroups * 각 subgroup의 sample size가 다르지만 , 하나의 고정된 컨트롤 리밋으로 작성하고 싶을 경우에는 ni의 평균을 사용하거나 가장.. 2024. 3. 25.
Control Chart for x_bar and R 컨트롤 차트 , X_bar and R​ - Suppose (xij, i=1..m j=1..n} are normally distributed - X bar chart monitors between-sample variability (variability over time) X bar 차트는 샘플들 간의 변동성을 나타내고 R chart measures within-sample variablitiy (intantaneous variability at a given time) R 차트는 샘플내의 변동성에 대해 측정한다. 1. Control chart for X_bar and R - Known μ and σ - Range Ri = max (x_ij) - min (x_ij) for j=1.. n - μ and σ을.. 2024. 3. 25.
Root Cause Analysis * Root and Cause Analysis , Continuous Improvement - To prevent recurrence at lowest cost in the simplest way 발본색원의 개념, 근원이 되는 문제를 제거해서 비슷한 문제들이 다시는 발생하지 않도록 방지하는 것 - method to trace down RC: data mining hierachial cluster solution (GT data mining) 1) Root cause: removed; prevent undesireable outcome,the condition that enable one or more causes 2) Casual cause: affect an event's outcome, but not.. 2024. 3. 25.
Dissimilarity Matrix - Dissimilarity Matrix (n objects x p attributes) : Store a collection of proximities that are available for all pairs of n objects A triangular matix, i.e., d(i,j) = d(j,i) d(i,j) is the measured dissimilarity or "differce" between objects i and j similarity measure sim(i,j) = 1 - d(i,j) d(i,j) is a non-negative number that is close to 0 when objects i and j are highly similar or "near" each ot.. 2024. 3. 25.
Basic Statistical Descriptions of Data - Quartiles : Q1 (25th percentile), Q3 (75th percentile) - Inter-quartile range: IQR = Q3- Q1 - Five number summary : min, Q1, median, Q3, max - Boxplot : ends of the box are the quartiles; median is marked ; add whiskers (minimum and maximum observation) ​ and plot outliers individually ; whiskers : 박스 바깥쪽에 가로로 나있는 선, 최소값과 최대값을 표시 - Outlier : usually, a value higer/ lower than 1.5 x IQR ex) 30,.. 2024. 3. 25.
Data Set, attributes - Data set 은 data objects로 이루어져 있고 data object는 entity 를 표현한다. ex) sales database: customers, store items, sales medical database: patients, treatments - Data objects는 attributes에 의해 설명된다. - Database의 row는 data objects로 columns는 attributes를 나타낸다. - Attribute 의 종류에는 1) Nominal 2) Binary 3) Ordinal 4) Numeric: quantitative 가 있다. 1) Nominal : categories, states or symbols - Hair_color = {auburn, bl.. 2024. 3. 25.
Interestingness Measure: Correlation Lift * Measure of dependent/correlated events: lift 1) Statistiacal independence P(S∩B) = P(S) x P(B) => Statistically independence P(S∩B) > P(S) x P(B) => Postively correlated P(S∩B) Negatively correlated 2) lift : interestingness measure: (interesting = reasonable 정도로 이해하면 될 것 같다) - if the lift is equal to 1, then A and B are independent and there is no correlation between them. A⊥.. 2024. 3. 25.
ECLAT ECLAT: Frequent Pattern Mining with Vertical Data Format * 기존의 Tid 순으로 표현했던 것을 각각의 아이템별로 Tid list 를 표현해낸다. - (K+1) 의 itemset 의 후보가 되려면 모든 K-item subset 이 frequent 해야한다. - Apriori 와는 달리 1) support 를 계산 하는데 짧은 시간이 걸린다. 2) 교집합을 찾기가 쉽다. 하지만 intermediate Tid 리스트가 너무 많은 메모리를 차지 할 수 있다. ex) minimum support count = 2 2024. 3. 25.
QALY (Quality - adjusted life year) QALY 에 대한 위키피디아의 정의는 아래와 같다. The quality-adjusted life year or quality-adjusted life-year (QALY) is a measure of disease burden, including both the quality and the quantity of life lived. It is used in assessing the value for money of a medical intervention. According to Pliskin et al., The QALY model requires utility independent, risk neutral, and constant proportional tradeoff behaviour. The Q.. 2024. 3. 5.
Critical Path Analysis Critical Path Analysis ex) 1. ES (earliest start) - Earliest start time given predecessor activities 2. EF (earliest finish) - Earliest possible completion time 3. LS (latest start) - Latest start time as to not delay entire project 4. LF (latest finish) - Latest finish time as to not delay entire project 1) Forward Pass ​- Proceed through diagram from strat to finish 다이아그램의 시작부터 시간을 계산해 나감 - ES.. 2024. 3. 5.
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