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The Digital Revolution and Climate Change
Published in Ron Basu, The Green Six Sigma Handbook, 2023
Minitab (Minitab.com) is a statistics package developed at Pennsylvania State University and distributed by Minitab LLC. This powerful statistical analysis package is a favourite with Six Sigma practitioners and offers three areas of functions—Discover, Predict and Achieve. Minitab can empower all parts of an organisation to predict better outcomes, design enhanced products and improve processes. It can access modern data analysis and explore data even further with advanced analytics and open-source integration. Visualisations can help present the findings through scatterplots, bubble plots, histograms, parallel plots, time series plots and more.
Minitab
Published in Paul W. Ross, The Handbook of Software for Engineers and Scientists, 2018
Minitab has a help system that explains how to use all of the built-in commands and explains other aspects of the system. Accessing it depends on the environment. For example, in Release 8 for DOS one types help commands at the Minitab prompt to obtain a listing of the categories of commands as shown below. MTB > help commandsTo get a list of the Minitab commands in one of the categories below, type HELP COMMANDS followed by the appropriate number, for example, HELP COMMANDS 1 for General Information.
Updates on electrospinning process models (part i)
Published in A. K. Haghi, Lionello Pogliani, Francisco Torrens, Devrim Balköse, Omari V. Mukbaniani, Andrew G. Mercader, Applied Chemistry and Chemical Engineering, 2017
Shima. Maghsoodlou, S. Poreskandar
where Y. is the achieved value in the experimental test and n is the number of tests. Equation 2.1 is used to calculate the S/N ratios of selected factors and their levels for final aim. The significance level of the variables for final aim was determined using the certain confidence level of the ANOVA. Software Minitab 14 was utilized to optimize the process according to the Taguchi approach. Minitab is strong software that is acknowledged to accurately solve numerous statistical issues and improve quality in the areas of engineering, statistics and mathematics.13, 14
A Comparison of In-vitro PAH Bioaccessibility in Historically Contaminated Soils: Implications for Risk Management
Published in Soil and Sediment Contamination: An International Journal, 2021
Atefeh Esmaeili, Oliver Knox, Albert Juhasz, Susan C. Wilson
Minitab (version 16, Minitab, LLC, USA) was used for all statistical analysis and data modeling. Differences between PAH concentrations extracted across methods and soils were assessed using one way ANOVA and t-tests, and data normality was established using the Ryan-Joiner normality test. Following each ANOVA, a Tukey post hoc test with p < .05 significance level was used for all parametric data. Kruskal-Wallis ANOVA and the two-sample rank test (Mann-Whitney test) were employed where data was found to be nonparametric. For data assessment, ring grouped PAHs included: 2–3 ring group PAHs as naphthalene; acenapthylene; acenapthene; fluorene; phenanthrene; anthracene; 4- ring group PAHs as fluoranthene; pyrene; benzo(a)anthracene; chrysene; 5–6 ring group PAHs as benzo(b)fluoranthene; benzo(k)fluoranthene; benzo(a)pyrene; dibenz(a,h)anthracene; benzo(ghi)perylene; indeno[1,2,3-cd]pyrene.
Improving patients’ satisfaction in a mobile hospital using Lean Six Sigma – a design-thinking intervention
Published in Production Planning & Control, 2020
Vijaya Sunder M, Sanjay Mahalingam, Sai Nikhil Krishna M
Lean Six Sigma tools such as project charter, process mapping, CTQ tree, VA-NVA analysis, process capability, QFD, and so on are used in the case study. These tools are used for diagnosing and resolving the set organizational problem from a Design-thinking perspective. Microsoft Excel is used to collate required data and perform basic analysis. Minitab, a statistical software, is used for graphical and statistical analysis. An overview of each stage of DMADV roadmap is presented below (Sunder 2016b; Zu, Fredendall, and Douglas 2008; Linderman et al. 2003).Define Phase – What is the problem? Does it exist?Measure Phase – How is the process measured? How is it performing?Analyze Phase – What are the causes of the problem? WHAT do customers want and HOW to address them?Design Phase – How to align customer’s requirements with design specifications? What is the prototype/design?Verify Phase – Is the design meeting customer needs? Does the design solve the problem in hand?
Modeling and Optimization of IoT Factors to Enhance Agile Manufacturing Strategy-based Production System Using SCM and RSM
Published in Smart Science, 2022
Umesh Kumar Vates, Bhupendra Prakash Sharma, Nand Jee Kanu, Eva Gupta, Gyanendra Kumar Singh
To validate the above data obtained from SCM, Response Surface Methodology (RSM) (UK 28; AD 29) is used using MiniTab [30]. Software is used. MiniTab is software used for solving and analyzing statistical problems and how to optimize these problems. The software is used both at the academic level and at the industrial level and across various sectors of manufacturing industries.