###155 In-Depth Statistical process control Questions for Professionals
####What is involved in Statistical Process control
Find out what the related areas are that Statistical Process control connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Statistical Process control thinking-frame.
####How far is your company on its Statistical process control journey?
Take this short survey to gauge your organization’s progress toward Statistical process control leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
####Start the Checklist
Below you will find a quick checklist designed to help you think about which Statistical Process control related domains to cover and 155 essential critical questions to check off in that domain.
The following domains are covered:
Statistical Process control, Process control, Automatic control, Check weigher, Chemical engineering, Closed-loop controller, Continuous production, Continuous stirred-tank reactor, Control engineering, Control loop, Control panel, Control system, Control theory, Control valve, Cruise control, Current loop, Digital control, Distributed Control System, Feed forward, Feedback control, Flow control valve, Fuzzy control system, Gain scheduling, Industrial control systems, Intelligent control, Laplace transform, Linear parameter-varying control, Measurement instrument, Model predictive control, Negative feedback, Nonlinear control, Open-loop controller, Operational historian, PID controller, Piping and instrumentation diagram, Positive feedback, Process capability, Process control monitoring, Programmable Logic Controller, Signal-flow graph, Simatic S5 PLC, Sliding mode control, Temperature control, Watt governor:
##Statistical Process control Critical Criteria:
Administer Statistical Process control leadership and modify and define the unique characteristics of interactive Statistical Process control projects.
– 29 Improving Capability. The center of the specifications for mesh tension in the previous exercise is 250 mV, but the center of our process is 275 mV. We can improve capability by adjusting the process to have center 250 mV. This is an easy adjustment that does not change the process variation. What percent of monitors now meet the new specifications?
– what is the best design framework for Statistical Process control organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
– Sower, V., J. Motwani, & M. Savoie. Are Acceptance Sampling and Statistical Process Control Complementary or Incompatible?
– Is the Statistical Process control organization completing tasks effectively and efficiently?
– Are Acceptance Sampling and Statistical Process Control Complementary or Incompatible?
– Why is product just outside specifications worse than product just inside specifications?
– How do we go about Comparing Statistical Process control approaches/solutions?
– You have just finished a project. Why did you start it?
– Is this product on spec?
– Special Cause Variation?
– Played darts?
##Process control Critical Criteria:
Grasp Process control decisions and budget the knowledge transfer for any interested in Process control.
– For your Statistical Process control project, identify and describe the business environment. is there more than one layer to the business environment?
– Do several people in different organizational units assist with the Statistical Process control process?
– Are the described activities consistent with current, accepted knowledge and ideas in the field?
– What threat is Statistical Process control addressing?
– How do you judge when a process is out of control?
– Where is Infor s Event Management targeted?
– Why study history of quality control?
– Was it developed with client input?
– WHAT IS ADVANCED CONTROL?
– What should we control?
##Automatic control Critical Criteria:
Cut a stake in Automatic control results and modify and define the unique characteristics of interactive Automatic control projects.
– How do you assess your Statistical Process control workforce capability and capacity needs, including skills, competencies, and staffing levels?
– Will Statistical Process control have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– Is there a Statistical Process control Communication plan covering who needs to get what information when?
##Check weigher Critical Criteria:
Adapt Check weigher visions and oversee implementation of Check weigher.
– How do you determine the key elements that affect Statistical Process control workforce satisfaction? how are these elements determined for different workforce groups and segments?
– How can we incorporate support to ensure safe and effective use of Statistical Process control into the services that we provide?
– Among the Statistical Process control product and service cost to be estimated, which is considered hardest to estimate?
##Chemical engineering Critical Criteria:
Demonstrate Chemical engineering risks and oversee Chemical engineering requirements.
– Using the preceding organizm, your boss would like you to design a continuous reactor system with an inlet flow and substrate concentration of 250 L/hr and 25 g/L, respectively, which will produce an overall yield of product of 2100 kg/yr, given an operating time of 300 day/yr at 24 hr/day. Assume no cells or product in the system inlet. Would you recommend a single fermenter of two fermenters in series?
– What are the key elements of your Statistical Process control performance improvement system, including your evaluation, organizational learning, and innovation processes?
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Statistical Process control processes?
– How is the rate equation developed by this model simplified to that by Scott et al. (1985) in the previous problem?
– What should be the size of the reactor if you employ a plug-flow reactor instead of the CSTR in part (a)?
– How can the rate equation derived in part (a) be simplified if ESP and EPS are the same?
– How can the system be operated and controlled for the maximum yield?
– What will drive Statistical Process control change?
– Whatisthemaximumreactionrate?
– Is this approach reliable?
##Closed-loop controller Critical Criteria:
Weigh in on Closed-loop controller management and report on developing an effective Closed-loop controller strategy.
– How do the Statistical Process control results compare with the performance of your competitors and other organizations with similar offerings?
– Who will provide the final approval of Statistical Process control deliverables?
– How is the value delivered by Statistical Process control being measured?
##Continuous production Critical Criteria:
Examine Continuous production goals and reduce Continuous production costs.
– Do we cover the five essential competencies-Communication, Collaboration, Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Statistical Process control in a volatile global economy?
– What is the difference between a continuous production process and an intermittent process, in manufacturing?
– How do we Lead with Statistical Process control in Mind?
– Where can a continuous production flow be applied?
##Continuous stirred-tank reactor Critical Criteria:
Accumulate Continuous stirred-tank reactor quality and revise understanding of Continuous stirred-tank reactor architectures.
– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Statistical Process control process. ask yourself: are the records needed as inputs to the Statistical Process control process available?
– What are our Statistical Process control Processes?
##Control engineering Critical Criteria:
Experiment with Control engineering engagements and raise human resource and employment practices for Control engineering.
– Has each emission unit proposed herein been evaluated for energy consumption including average and peak electrical use; efficiency of electric motors and suitability of alternative motors such as variable speed; added heat load and/or added cooling load as a result of the operation of the proposed process; added energy load due to building air exchange requirements as a result of exhausting heat or emissions to the ambient air; and/or use of compressors?
– What does an human, animal or machine do so that it reaches an end through variable means?
– What are the barriers to increased Statistical Process control production?
– Does (do) the secondary burner(s) remain on for the duration of the burn?
– Why is Statistical Process control important for you now?
– Any Photochemically Reactive Materials Used on Press?
– Continuous Temperature Recorder for Primary Chamber?
– How many cremation units are to be installed?
– What is a control system?
– Other?
##Control loop Critical Criteria:
Examine Control loop issues and adopt an insight outlook.
– Who will be responsible for deciding whether Statistical Process control goes ahead or not after the initial investigations?
– Given the advantages of system openness, why did MENA still select a closed control loop in supervising its IPs?
– How can the value of Statistical Process control be defined?
##Control panel Critical Criteria:
Analyze Control panel governance and define Control panel competency-based leadership.
– We know how to do this via the Control Panel, and are prepared to bet that the setting is stored somewhere in the registry. This makes this task an ideal candidate for auditing, so here goes: The first question we need to ask is what key should we set auditing on?
– There is an option that can be set via the Control Panel that specifies how long a machine should wait for user input before proceeding with the default hardware profile selection at boot time. Where in the registry is this value set?
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Statistical Process control models, tools and techniques are necessary?
– What are the short and long-term Statistical Process control goals?
– Is a Statistical Process control Team Work effort in place?
– Control panel Help (?
##Control system Critical Criteria:
Chat re Control system strategies and get going.
– Has your organization conducted a cyber risk or vulnerability assessment of its information systems, control systems, and other networked systems?
– How can you experiment with a complex change and benefit from the version control system without making the change public?
– How do we ensure that implementations of Statistical Process control products are done in a way that ensures safety?
– Does Statistical Process control create potential expectations in other areas that need to be recognized and considered?
– How do we Identify specific Statistical Process control investment and emerging trends?
– Is Cybersecurity integrated between business systems and control systems?
– What is a Management Control System?
– What is your quality control system?
##Control theory Critical Criteria:
Disseminate Control theory outcomes and suggest using storytelling to create more compelling Control theory projects.
– Control theory provides sound and rigorous mathematical principles to analyze dynamical systems, and design controllers for them. While it is widely used in mechanical, aeronautical, and chemical engineering 2, there is concern with applying standard linear control techniques to computer systems, a domain in which non-linearities abound. Although there is a well-developed theory of non-linear control, it is much more difficult to apply, does not generalize across systems, and provides much less insight than linear control theory. Hence, we adopt a pragmatic perspective. Can we construct and analyze the properties of real-life closed-loop computer systems using linear control theory?
– In engineering, control theory is based on the concept of monitoring. An engineer might want to be able to tune his factory:How can I control this plastic film extruder to ensure a uniform thickness of plastic?
– How do your measurements capture actionable Statistical Process control information for use in exceeding your customers expectations and securing your customers engagement?
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Statistical Process control services/products?
– Can we construct and analyze the properties of real-life closed-loop computer systems using linear control theory?
– How to deal with Statistical Process control Changes?
##Control valve Critical Criteria:
Accumulate Control valve tactics and arbitrate Control valve techniques that enhance teamwork and productivity.
– What knowledge, skills and characteristics mark a good Statistical Process control project manager?
– Does the Statistical Process control task fit the clients priorities?
– What turbocharger control valves are needed for proper engine operation?
– How can you measure Statistical Process control in a systematic way?
##Cruise control Critical Criteria:
Guard Cruise control decisions and slay a dragon.
– Risk factors: what are the characteristics of Statistical Process control that make it risky?
– What potential environmental factors impact the Statistical Process control effort?
##Current loop Critical Criteria:
Accumulate Current loop visions and define Current loop competency-based leadership.
– How do you manage and improve your Statistical Process control work systems to deliver customer value and achieve organizational success and sustainability?
– What are the business goals Statistical Process control is aiming to achieve?
##Digital control Critical Criteria:
Wrangle Digital control engagements and find the ideas you already have.
– Apple has a smaller market share but leads in profit share in the mobile industry because it earns its profits not only through its product (iPhone and iOS) but receives a share of the follow-on revenue that the telecom carriers earn from the end users. Unlike other handset manufacturers, such as Samsung and HTC, Apples appeal to the end consumer is arguably higher. This control of the industry architecture allows Apple to extract a higher premium. Is Apples place in the telecom industry an outlier or an early indication of how we could see more companies that redefine industry architecture with digital control points and extract a disproportionate share of profit?
– Do the Statistical Process control decisions we make today help people and the planet tomorrow?
##Distributed Control System Critical Criteria:
Debate over Distributed Control System visions and create a map for yourself.
– For engineering purposes, we need much better tools for predicting emergent behavior of complex systems from their components. An analogy with reaction diffusion systems makes this evident in the design of distributed control systems. Turing demonstrated that diffusion can lead to spatial patterns in a chemically reacting system even when the homogeneous system of reactions has a globally stable equilibrium state. This happens despite the fact that diffusion usually acts to make concentrations more uniform. In the Turing example, different diffusion rates of an activator and inhibitor destabilize a spatially homogeneous equilibrium state. How do we avoid this type of instability that arises from the coupling of large numbers of stable components in systems like the power grid or a commercial building?
– What other jobs or tasks affect the performance of the steps in the Statistical Process control process?
– Are assumptions made in Statistical Process control stated explicitly?
##Feed forward Critical Criteria:
Map Feed forward leadership and suggest using storytelling to create more compelling Feed forward projects.
– Will new equipment/products be required to facilitate Statistical Process control delivery for example is new software needed?
– Are there Statistical Process control Models?
##Feedback control Critical Criteria:
Consult on Feedback control risks and devise Feedback control key steps.
– In addition to the natural response of a system, we are also interested in understanding how it responds to input. For example, what is the motion of the spacecraft attitude in response to repeated gas jet firing or to slowly varying aerodynamic drag, or to sudden retargeting commands in a feedback control system?
– Is maximizing Statistical Process control protection the same as minimizing Statistical Process control loss?
– Does Statistical Process control analysis isolate the fundamental causes of problems?
– Why feedback control ?
##Flow control valve Critical Criteria:
Start Flow control valve planning and find answers.
##Fuzzy control system Critical Criteria:
Analyze Fuzzy control system outcomes and triple focus on important concepts of Fuzzy control system relationship management.
– Think about the functions involved in your Statistical Process control project. what processes flow from these functions?
– How does the organization define, manage, and improve its Statistical Process control processes?
##Gain scheduling Critical Criteria:
Map Gain scheduling management and figure out ways to motivate other Gain scheduling users.
– At what point will vulnerability assessments be performed once Statistical Process control is put into production (e.g., ongoing Risk Management after implementation)?
– In what ways are Statistical Process control vendors and us interacting to ensure safe and effective use?
##Industrial control systems Critical Criteria:
Accelerate Industrial control systems leadership and adopt an insight outlook.
– Do those selected for the Statistical Process control team have a good general understanding of what Statistical Process control is all about?
– What are your key Statistical Process control organizational performance measures, including key short and longer-term financial measures?
– What are our needs in relation to Statistical Process control skills, labor, equipment, and markets?
##Intelligent control Critical Criteria:
Guard Intelligent control quality and track iterative Intelligent control results.
– Who will be responsible for making the decisions to include or exclude requested changes once Statistical Process control is underway?
– What prevents me from making the changes I know will make me a more effective Statistical Process control leader?
##Laplace transform Critical Criteria:
Set goals for Laplace transform visions and devise Laplace transform key steps.
– What tools do you use once you have decided on a Statistical Process control strategy and more importantly how do you choose?
– Will Statistical Process control deliverables need to be tested and, if so, by whom?
– Is Supporting Statistical Process control documentation required?
##Linear parameter-varying control Critical Criteria:
Read up on Linear parameter-varying control governance and triple focus on important concepts of Linear parameter-varying control relationship management.
– Which Statistical Process control goals are the most important?
##Measurement instrument Critical Criteria:
Think about Measurement instrument quality and visualize why should people listen to you regarding Measurement instrument.
– Whenever a measurement instrument (such as a questionnaire) is changed between the pretest and the posttest, this change is likely to result in an effect that is independent of any effect due to a program or project. For example, if knowledge of family planning is measured on the pretest by the-questionHave you ever-heard of-family-planning?
– What tools and technologies are needed for a custom Statistical Process control project?
– How do we Improve Statistical Process control service perception, and satisfaction?
##Model predictive control Critical Criteria:
Design Model predictive control planning and look at it backwards.
– What are the long-term Statistical Process control goals?
##Negative feedback Critical Criteria:
Ventilate your thoughts about Negative feedback leadership and ask what if.
– The activity of an agent may eventually reflect back on itself. A good investment can produce good returns (positive feedback), and overspending can result in a shortage in the money supply (negative feedback). Without feedback there would be no economic system who would invest if there were no returns?
– How are retailers using Social media to track and improve brand presence and Sales Apart from tracking positive and negative feedback and sentiment analysis?
– In spite of the need to address poor performance, managers are usually not very comfortable providing negative feedback. Why is this so?
– How might you give unsolicited negative feedback to someone on your project team who is making others tasks more difficult?
– What happens when managers avoid giving negative feedback and employees avoid seeking it?
##Nonlinear control Critical Criteria:
Do a round table on Nonlinear control projects and grade techniques for implementing Nonlinear control controls.
– How do we make it meaningful in connecting Statistical Process control with what users do day-to-day?
##Open-loop controller Critical Criteria:
Have a session on Open-loop controller engagements and probe Open-loop controller strategic alliances.
– What is the source of the strategies for Statistical Process control strengthening and reform?
– How can we improve Statistical Process control?
##Operational historian Critical Criteria:
Inquire about Operational historian projects and suggest using storytelling to create more compelling Operational historian projects.
– Are accountability and ownership for Statistical Process control clearly defined?
– How do we accomplish our long range Statistical Process control goals?
##PID controller Critical Criteria:
Rank PID controller failures and get the big picture.
– What are the record-keeping requirements of Statistical Process control activities?
– Why should we adopt a Statistical Process control framework?
##Piping and instrumentation diagram Critical Criteria:
Merge Piping and instrumentation diagram outcomes and simulate teachings and consultations on quality process improvement of Piping and instrumentation diagram.
– What management system can we use to leverage the Statistical Process control experience, ideas, and concerns of the people closest to the work to be done?
– Are there any disadvantages to implementing Statistical Process control? There might be some that are less obvious?
– How will you know that the Statistical Process control project has been successful?
##Positive feedback Critical Criteria:
Win new insights about Positive feedback leadership and prioritize challenges of Positive feedback.
– If your company is already highly profitable, staff may not have a strong inclination to reduce operating or production costs by, for example, switching off equipment when not in use – especially if the shareholders rather than their own pay packets benefit from cost-saving measures. However, informing staff of the environmental impacts of the organization (for example carbon dioxide emissions or waste volumes going to landfill) and how staff have an important role in reducing these can be an effective motivator – especially as environmental awareness continues to increase in the general population. The positive feedback to staff of reductions in harmful environmental impacts can increase this motivation (Havent we done well, can we keep this up and do better?
– The positive feedback to staff of reductions in harmful environmental impacts can increase this motivation (Havent we done well, can we keep this up and do better?
– When a Statistical Process control manager recognizes a problem, what options are available?
##Process capability Critical Criteria:
Systematize Process capability visions and prioritize challenges of Process capability.
– Before entering into a contract, a company should ask these questions: Does the contract manufacturer have the capability to do change control, corrective or preventive action, or process capability studies?
– Can we add value to the current Statistical Process control decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?
– Is there any existing Statistical Process control governance structure?
– Current Process Capability How is the process performing today?
##Process control monitoring Critical Criteria:
Inquire about Process control monitoring issues and reduce Process control monitoring costs.
– How do you use Statistical Process control data and information to support organizational decision making and innovation?
– How can you negotiate Statistical Process control successfully with a stubborn boss, an irate client, or a deceitful coworker?
– What are your most important goals for the strategic Statistical Process control objectives?
##Programmable Logic Controller Critical Criteria:
Adapt Programmable Logic Controller issues and ask questions.
– How would one define Statistical Process control leadership?
##Signal-flow graph Critical Criteria:
Jump start Signal-flow graph issues and oversee Signal-flow graph management by competencies.
– What new services of functionality will be implemented next with Statistical Process control ?
##Simatic S5 PLC Critical Criteria:
Design Simatic S5 PLC visions and question.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Statistical Process control. How do we gain traction?
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Statistical Process control processes?
##Sliding mode control Critical Criteria:
Air ideas re Sliding mode control strategies and learn.
– What are the success criteria that will indicate that Statistical Process control objectives have been met and the benefits delivered?
– Do you monitor the effectiveness of your Statistical Process control activities?
##Temperature control Critical Criteria:
Be clear about Temperature control projects and reduce Temperature control costs.
– Think about the people you identified for your Statistical Process control project and the project responsibilities you would assign to them. what kind of training do you think they would need to perform these responsibilities effectively?
– The key question for determining a potential water temperature compliance location is how much coldwater is available at shasta reservoir to manage through the may to october water temperature control season?
– What are specific Statistical Process control Rules to follow?
##Watt governor Critical Criteria:
Deliberate Watt governor engagements and assess and formulate effective operational and Watt governor strategies.
– How important is Statistical Process control to the user organizations mission?
###Conclusion:
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Statistical process control Self Assessment:
store.theartofservice.com/Statistical-process-control-A-Complete-Guide/
Author: Gerard Blokdijk
CEO at The Art of Service | theartofservice.com
www.linkedin.com/in/gerardblokdijk
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
###External links:
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
##Statistical Process control External links:
Statistical Process Control (SPC) Tutorial – MoreSteam
www.moresteam.com/toolbox/statistical-process-control-spc.cfm
Statistical Process Control based on SPC 2 nd Edition
walter-oldeck.squarespace.com/s/SPC-Webinar-core-tools.pdf
Xerox: Introduction to Statistical Process Control – Conduent
www.statit.com/services/SPCOverview_mfg.pdf
##Process control External links:
Statistical Process Control (SPC) Tutorial – MoreSteam
www.moresteam.com/toolbox/statistical-process-control-spc.cfm
Process Control | Standard Controls
www.standardcontrols.com/process-control
##Automatic control External links:
Automatic Control – PID Control
www.control.lth.se/Research/ProcessControl/PIDControl
##Check weigher External links:
Patent US4231439 – Automatic check weigher – Google Patents
www.google.com/patents/US4231439
NEWTEC – Check weighers
www.newtec.com/machines/check-weighers
US4231439A – Automatic check weigher – Google Patents
patents.google.com/patent/US4231439A/en
##Chemical engineering External links:
Pocket Guide to Chemical Engineering – CNTQ
cntq.gob.ve/cdb/documentos/quimica/214.pdf
Chemical Engineering Journal – Elsevier
www.journals.elsevier.com/chemical-engineering-journal
MEng (Hons) Chemical Engineering – Newcastle University
www.ncl.ac.uk/undergraduate/degrees/h813
##Continuous stirred-tank reactor External links:
Continuous Stirred-tank Reactor – liquisearch.com
www.liquisearch.com/continuous_stirred-tank_reactor
##Control loop External links:
Control Loop Cookbook – ENCON – courses
encon.fke.utm.my/nikd/Dc_dc_converter/TI-SEM/slup113.pdf
Critical components of a surge control loop – Control Global
www.controlglobal.com/articles/2005/575
##Control panel External links:
Control Panels – P & I Critical Power Specialists
www.pandigroup.co.uk/control-panels
Where is Control Panel? – Windows Help – Microsoft Support
support.microsoft.com/en-au/help/13764
Mission Critical X-keys Control Panels
xkeys.com/XkeysApplications/MissionCritical.php
##Control system External links:
Critical Assessment of Damage Control System Technologies
cradpdf.drdc-rddc.gc.ca/PDFS/unc63/p527467.pdf
Control systems with quasi-critical damping – IOPscience
iopscience.iop.org/article/10.1088/0508-3443/5/5/304/pdf
FRAMEWORK FOR THE EVALUATION OF INTERNAL CONTROL SYSTEMS
www.bis.org/publ/bcbs33.pdf
##Control theory External links:
control theory | mathematics | Britannica.com
www.britannica.com/topic/control-theory-mathematics
The gate-control theory of pain. A critical review.
www.ncbi.nlm.nih.gov/pubmed/183859
Evaluation of the Gate Control Theory
gatecontrolpaintheory.weebly.com/evaluation.html
##Control valve External links:
8 Critical Control Valve Selection Criteria – Swanson Flo
blog.swansonflo.com/2017/09/8-critical-control-valve-selection.html
Control Valve Handbook Third Edition (5.86 MB pdf)
www.pacontrol.com/download/Emerson-Control-Valve-HandBook.pdf
guidelines for minimum flow control valves rev 1 – HORA
www.hora.de/fileadmin/downloads/produkte/Baureihe_86.pdf
##Cruise control External links:
Rostra 250-1223 Universal Cruise Control System
www.rostra.com/universal-aftermarket-cruise-control-by-rostra.php
product photos – Harley Cruise control
www.harleycruisecontrol.com/product.html
Cruise Control Diet Review | Legit Healthy Weight Loss Plan?
##Distributed Control System External links:
Distributed Control System Operations | SpringerLink
link.springer.com/chapter/10.1007/978-3-319-02889-7_3
##Feed forward External links:
Feedback and feed forward | Jisc
www.jisc.ac.uk/guides/feedback-and-feed-forward
##Feedback control External links:
Feedback Control Theory
www.control.utoronto.ca/people/profs/francis/dft.pdf
##Flow control valve External links:
guidelines for minimum flow control valves rev 1 – HORA
www.hora.de/fileadmin/downloads/produkte/Baureihe_86.pdf
##Fuzzy control system External links:
8. The Stability of Fuzzy Control Systems – Springer
link.springer.com/content/pdf/10.1007/978-3-7908-1824-6_8.pdf
Stability analysis of fuzzy control systems – ScienceDirect
www.sciencedirect.com/science/article/pii/S0165011497002340
FUZZY CONTROL SYSTEMS DESIGN AND ANALYSIS
saba.kntu.ac.ir/eecd/taghirad/E books/TOC/Fuzzy Expert Systems.pdf
##Industrial control systems External links:
Guide to Industrial Control Systems (ICS) Security
nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-82r2.pdf
A Survey of Industrial Control Systems Security
www.cse.wustl.edu/~jain/cse571-11/ftp/ics/index.html
For Industrial Control Systems – DataDiode
www.fox-it.com/datadiode/for-industrial-control-systems
##Intelligent control External links:
Intelligent Control | IEEE Control Systems Society
www.ieeecss.org/technical-activities/intelligent-control
OneConnect intelligent control plane – Ciena
www.ciena.com/products/one-connect
An intelligent control system for ventilators – ScienceDirect
www.sciencedirect.com/science/article/pii/S1350453398000484
##Laplace transform External links:
Laplace transforms and it?s Applications in Engineering Field
ijcotjournal.org/2015/volume-19/number-1/IJCOT-V19P310.pdf
MATLAB Central – Numerical Laplace transform
www.mathworks.com/matlabcentral/newsreader/view_thread/327982
Laplace Transform – UUMath – University of Utah
www.math.utah.edu/~gustafso/laplaceTransform.pdf
##Model predictive control External links:
Economic Model Predictive Control – A Review
www.iaarc.org/publications/fulltext/isarc2014_submission_222.pdf
ROBUST MODEL PREDICTIVE CONTROL FOR INPUT …
www.ajc.org.tw/pages/PAPER/7.3PD/AC0703-P319-FR0380R-b.pdf
MODEL PREDICTIVE CONTROL USING FPGA
airccse.org/journal/ijctcm/papers/5215ijctcm01.pdf
##Negative feedback External links:
The Value of Negative Feedback—When It’s Done Well
playbook.amanet.org/training-articles-value-negative-feedback
Critical Path /// Negative Feedback
www.criticalpathproject.com/video/negative-feedback
##Nonlinear control External links:
NONLINEAR CONTROL SYSTEMS – crcnetbase.com
www.crcnetbase.com/doi/pdf/10.1201/9780203912652.ch6
NONLINEAR CONTROL SYSTEM DESIGN USING VARIABLE …
www.scielo.br/pdf/ca/v17n1/a03v17n1.pdf
Jump Resonance Criteria of Nonlinear Control Systems
www.jstage.jst.go.jp/article/sicetr1965/1/4/1_4_304/_article
##PID controller External links:
PERFORMANCE ASSESSMENT OF PID CONTROLLERS
www.ece.ualberta.ca/~marquez/papers/wen_cis_04.pdf
Auto Tuning PID Controller for Multi-tank Process
research.ijcaonline.org/volume84/number4/pxc3892673.pdf
Tuning PID Controllers using the ITAE Criterion* – ijee.ie
www.ijee.ie/articles/Vol21-5/Ijee1673.pdf
##Piping and instrumentation diagram External links:
Piping and Instrumentation Diagram | PIPING GUIDE
www.pipingguide.net/2008/12/piping-instrumentation-diagram.html
Basic Knowledge About Piping and Instrumentation Diagram
www.edrawsoft.com/knowing-pid.php
P & ID – Piping and Instrumentation Diagram – IBI Chematur
www.ibichematur.com/intelligient-p-id.htm
##Positive feedback External links:
Selection Criteria: The art of giving positive feedback
www.selectioncriteria.com.au/a-feedback.html
critical mass – Positive Feedback
positive-feedback.com/Issue40/critical_mass.htm
Positive Feedback – Mission Critical Training
www.mcstech.net/positive-feedback
##Process capability External links:
6.1.6. What is Process Capability? – itl.nist.gov
www.itl.nist.gov/div898/handbook/pmc/section1/pmc16.htm
Measuring Your Process Capability – Symphony
www.symphonytech.com/articles/pdfs/processcapability.pdf
Process Capability Analysis and Process Analytical Technology
statisticaloutsourcingservices.com/Capability.pdf
##Programmable Logic Controller External links:
PLC Programming | Programmable Logic Controller Basics
www.galco.com/comp/prod/plc.htm
PROGRAMMABLE LOGIC CONTROLLERS – Schneider Electric
static.schneider-electric.us/docs/csi-specifications/40 94 43.01.doc
Programmable Logic Controller (PLC) – WIRED
www.wired.com/2012/04/exploit-for-quantum-plc
##Sliding mode control External links:
Sliding Mode Control Of SMPS – IOSR Journals
iosrjournals.org/iosr-jeee/Papers/Vol4-issue5/A0450111.pdf
MATLAB Central – Sliding Mode Control – MathWorks
www.mathworks.com/matlabcentral/newsreader/view_thread/504
Modified Chattering Free Sliding Mode Control of DC Motor
www.ijmer.com/papers/Vol3_Issue3/BF3314191423.pdf
##Temperature control External links:
FAST TRACK PAVING: CONCRETE TEMPERATURE CONTROL …
www.hiperpav.com/downloads/FHWA-RD-98-168.pdf
FAST TRACK PAVING: CONCRETE TEMPERATURE CONTROL …
www.hiperpav.com/downloads/FHWA-RD-98-167.pdf