problem solving industrial engineering

Mastering Problem-Solving: 7 Steps Every Industrial Engineer Should Know

Introduction Problem-Solving in Industrial Engineering

As an industrial engineer, mastering problem-solving skills is paramount for navigating the complex challenges inherent in the field. With a strategic approach encompassing seven essential steps, you can confront any obstacle with confidence and efficiency. Firstly, thorough problem definition is key; understanding the root cause and scope of the issue lays the foundation for effective solutions. Following this, meticulous data collection and analysis provide the necessary insights to devise informed strategies. Utilizing various analytical tools and methodologies, such as statistical analysis or simulation techniques, enhances the accuracy of your problem-solving process.

Once armed with data-driven insights, brainstorming and evaluating potential solutions become the next crucial steps. Encouraging diverse perspectives and collaboration fosters creativity and generates innovative ideas. Prioritizing solutions based on feasibility, cost-effectiveness, and impact ensures that resources are allocated effectively. Implementing the chosen solution with clear communication and project management ensures smooth execution. Additionally, continuous monitoring and evaluation allow for adjustments as needed, ensuring sustained success and improvement over time. By adhering to these fundamental steps, industrial engineers can tackle any challenge with resilience and proficiency, driving progress and innovation in their field.

Step 1: Clearly Define the Problem

Before embarking on the journey of problem-solving, it is imperative to meticulously define the issue at hand. Take ample time to delve into the intricacies of the problem, understanding its root cause and comprehending its implications on the broader process or system. This initial step sets the stage for the entire problem-solving process, as a thorough understanding of the problem is essential for devising effective solutions. Engage stakeholders and subject matter experts to gather diverse perspectives and insights, ensuring a comprehensive grasp of the problem’s nuances. By investing time and effort in this preliminary stage, you lay a solid foundation for the subsequent steps, facilitating a more streamlined and targeted approach to problem resolution.

Step 2: Gather Relevant Data and Information

Armed with a clear understanding of the problem, the next step in the problem-solving process is to gather all pertinent data and information. This step is crucial as it provides the raw material necessary for informed decision-making. Cast a wide net when collecting data, ensuring that all relevant sources are explored and considered. Whether it involves analyzing production logs, conducting surveys, or leveraging existing databases, the goal is to gather comprehensive and accurate information.

Once data is collected, it’s essential to analyze it thoroughly to uncover patterns, trends, and correlations that offer insights into the underlying dynamics of the problem. Utilize analytical tools and techniques such as statistical analysis, data visualization, and trend analysis to extract meaningful information from the raw data. By meticulously examining the data, you can identify key factors contributing to the problem and gain valuable insights that will guide your subsequent solution development efforts. This rigorous data-driven approach enhances the likelihood of devising effective and sustainable solutions that address the root cause of the problem.

Step 3: Brainstorm Solutions

With a thorough understanding of the problem and relevant data in hand, the next pivotal step is to engage in a structured brainstorming session to generate potential solutions. Brainstorming serves as a creative platform where engineers can unleash their ingenuity and explore diverse avenues for problem resolution. Encourage an open and inclusive atmosphere where team members feel empowered to share their ideas, no matter how unconventional they may seem.

During the brainstorming process, it’s essential to consider a wide range of approaches and perspectives. Encourage participants to think outside the box and challenge conventional wisdom. By fostering a spirit of innovation and curiosity, engineers can unearth novel insights and possibilities that may have been overlooked initially. Embrace the principle of quantity over quality during this stage, as generating a plethora of ideas provides a rich pool from which to draw inspiration.

As ideas are generated, capture them in a systematic manner, whether through brainstorming sessions, virtual collaboration tools, or whiteboard sessions. Once all ideas are on the table, evaluate each one critically, considering its feasibility, potential impact, and alignment with organizational goals. By leveraging the collective creativity and expertise of the team, engineers can identify promising solutions that have the potential to address the problem effectively and drive positive outcomes.

Step 4: Evaluate and Select the Best Solution

After an exhaustive brainstorming session yielding a variety of potential solutions, the critical next phase involves evaluating and selecting the most suitable option. This step requires a meticulous assessment of each proposed solution, taking into account factors such as feasibility, cost-effectiveness, and potential impact on the overall process or system.

Engineers must conduct a comprehensive analysis of each solution, considering its technical feasibility, resource requirements, and compatibility with existing infrastructure. Additionally, evaluating the anticipated costs associated with implementation, including both initial investment and ongoing operational expenses, is paramount. Balancing these factors against the expected benefits and potential risks helps in determining the overall viability of each solution.

Furthermore, it’s essential to assess the potential impact of each solution on the broader context, including its alignment with organizational goals, regulatory compliance, and stakeholder preferences. Conducting a thorough risk analysis to anticipate and mitigate any potential drawbacks or unintended consequences is also crucial.

Once all options have been carefully evaluated, the final selection should be made based on a holistic consideration of all relevant factors. This decision-making process may involve consulting with stakeholders, subject matter experts, and other relevant parties to ensure consensus and buy-in.

By following a systematic approach to evaluate and select the best solution, engineers can make informed decisions that not only address the immediate problem but also contribute to long-term success and sustainability.

Step 5: Develop an Action Plan

Once the optimal solution has been identified, the next pivotal step is to craft a comprehensive action plan delineating the necessary steps for its implementation. Developing a detailed action plan is essential for ensuring a structured and systematic approach to executing the chosen solution effectively.

Start by clearly defining the objectives and desired outcomes of the action plan. Establish specific, measurable, achievable, relevant, and time-bound (SMART) goals that serve as benchmarks for success. These goals provide a clear roadmap for progress and help keep the implementation process on track.

Next, outline the specific tasks and activities required to implement the solution. Break down the overall project into smaller, manageable components, assigning responsibilities and deadlines to relevant team members or stakeholders. Clearly define roles and expectations to ensure accountability and facilitate smooth coordination among team members.

In addition to outlining tasks and responsibilities, it’s essential to establish a realistic timeline for implementation. Consider factors such as resource availability, dependencies between tasks, and potential obstacles that may impact the project timeline. By setting achievable milestones and deadlines, you can maintain momentum and track progress throughout the implementation process.

Moreover, incorporate mechanisms for monitoring and evaluating progress into the action plan. Define key performance indicators (KPIs) or metrics that will be used to assess the effectiveness of the solution and measure its impact on the desired outcomes. Regularly review progress against these KPIs and make adjustments as needed to stay aligned with project goals.

Finally, communicate the action plan clearly to all stakeholders involved, ensuring everyone understands their roles, responsibilities, and expectations. Foster open communication channels to facilitate collaboration and address any concerns or challenges that may arise during implementation.

By developing a well-defined action plan, engineers can navigate the implementation process with confidence and efficiency, ultimately leading to the successful resolution of the identified problem.

Step 6: Implement the Solution

With the action plan meticulously crafted, it’s time to transition from planning to action by implementing the chosen solution. This phase marks the culmination of the problem-solving process and requires diligent oversight and proactive management from industrial engineers.

First and foremost, it’s essential for engineers to assume a leadership role in overseeing the execution of the solution. Assign responsibilities to relevant team members according to the action plan, ensuring clarity regarding roles and expectations. Maintain open lines of communication to facilitate collaboration and address any concerns or obstacles that may arise during implementation.

As the solution is rolled out, monitor progress closely to ensure that tasks are being completed according to schedule and quality standards. Keep stakeholders informed of milestones reached and any significant developments, fostering transparency and maintaining stakeholder engagement throughout the process.

Flexibility is also key during the implementation phase, as unforeseen challenges or opportunities may emerge. Be prepared to make adjustments to the action plan as needed, reallocating resources or revising timelines to address evolving circumstances while staying aligned with project objectives.

Effective communication and coordination are paramount throughout the implementation process. Regularly convene status meetings or check-ins to provide updates, solicit feedback, and address any issues or concerns in a timely manner. Foster a collaborative environment where team members feel empowered to contribute their insights and expertise towards achieving common goals.

By assuming a proactive and hands-on approach to implementation, industrial engineers can ensure that the chosen solution is executed successfully, delivering tangible results and driving positive outcomes for the organization.

Step 7: Evaluate the Results

As the implemented solution begins to take effect, the final critical step in the problem-solving process is to evaluate its results comprehensively. Engineers must assess the outcomes against the predetermined objectives, gathering feedback and insights from stakeholders and team members involved in the implementation process.

Start by conducting a thorough analysis of the results achieved, comparing them to the initial goals and performance metrics outlined in the action plan. Evaluate both quantitative and qualitative data to gain a holistic understanding of the solution’s impact on the problem at hand and the broader operational context.

In addition to analyzing outcomes, seek feedback from stakeholders, including end-users, supervisors, and other relevant parties, to gather diverse perspectives on the effectiveness of the solution. Solicit insights regarding areas of success, challenges encountered, and suggestions for improvement.

Moreover, take the time to reflect critically on the implementation process itself, identifying any bottlenecks, inefficiencies, or lessons learned that can inform future problem-solving endeavors. Consider factors such as communication strategies, resource allocation, and project management techniques to pinpoint areas for optimization and refinement.

Based on the evaluation findings, develop actionable recommendations for refining the implemented solution or addressing any remaining gaps or issues. Implement iterative improvements based on these recommendations to continuously enhance the effectiveness and efficiency of the solution over time.

Furthermore, document the lessons learned and best practices gleaned from the problem-solving process to inform future endeavors and build organizational knowledge and capabilities. Foster a culture of continuous learning and improvement within the engineering team, encouraging ongoing reflection and adaptation.

By rigorously evaluating the results of the implemented solution, engineers can extract valuable insights and lessons that inform future problem-solving efforts, driving continuous improvement and innovation within the organization.

In conclusion, mastering problem-solving is indeed a dynamic and ongoing journey that demands a blend of critical thinking, creativity, and analytical prowess. Through the diligent application of the seven steps outlined—clearly defining the problem, gathering relevant data, brainstorming solutions, evaluating and selecting the best option, developing a comprehensive action plan, implementing the chosen solution, and evaluating the results—industrial engineers can elevate their problem-solving capabilities to new heights.

By embracing this systematic approach, engineers can not only address immediate challenges but also foster a culture of innovation and continuous improvement within their organizations. This structured methodology empowers engineers to tackle complex problems with confidence and efficiency, driving positive change and contributing to the overall success and competitiveness of their organizations.

Ultimately, the mastery of problem-solving is not merely about finding solutions to individual challenges but about cultivating a mindset of inquiry, adaptability, and resilience. By honing their problem-solving skills through practice, reflection, and collaboration, industrial engineers can position themselves as catalysts for positive change, driving innovation and progress in their fields and beyond.

Application of 7-Step Problem-Solving Methodology for Defect Elimination: A Case Study in an Automotive Industry | SpringerLink

(PDF) Industrial engineers articulate their critical thinking for problem solving via the D.R.I.V.E.S. model (researchgate.net)

What is Problem Solving? – Introduction to Industrial Engineering (pressbooks.pub)

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Introduction to Industrial Engineering

(2 reviews)

Bonnie Boardman

Copyright Year: 2020

ISBN 13: 9781648169823

Publisher: Mavs Open Press

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Polinpapilinho Katina, Assistant Professor, USC-Upstate on 5/21/21

The text covers all areas and ideas of the subject of industrial engineering appropriately and provides an effective index and/or glossary. However, the logical progressional of chapters could be aided by first providing the foundational... read more

Comprehensiveness rating: 4 see less

The text covers all areas and ideas of the subject of industrial engineering appropriately and provides an effective index and/or glossary. However, the logical progressional of chapters could be aided by first providing the foundational information (e.g., Systems Thinking) and then progressing into the core of industrial engineering.

Content Accuracy rating: 5

The text covers well the selected topics (i.e., Industrial Engineering, Teamwork, Problem Solving, Big Ideas in Industrial Engineering, Using Models, Deming’s 14 Points, People in the System, Systems Thinking, Lean Operations, The IE Approach, Organizations’ Missions, Visions, and Values, Lifelong Learning). An undergraduate student is provided enough details to grasp the fundamentals of IE and leave them wanting to know more about IE.

Relevance/Longevity rating: 4

The content of this textbook is the stake of current knowledge on the topics selected. Moreover, the book is written in such a manner that it can easily compare emerging topics (e.g., industrial vulnerability, industry 4.0). These could easily be included in Chapter 4. Any necessary updates will be relatively easy and straightforward to implement.

Clarity rating: 5

The text is written in accessible prose and provides adequate context for any jargon/technical terminology used, meaning that any undergraduate student should be able to understand the content and context. In any area that the student is not fluid, certainly, the instructor will be able to explain.

Consistency rating: 5

From the get-go, the text is internally consistent in terms of terminology and the IE framework. Words such as “system” and “safety” are defined in chapter 1 and are used consistently.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections assigned at different points within the course. In fact, many of the chapters are relatively small that they could be read and discussed in a short period of time.

Organization/Structure/Flow rating: 4

For a large part, the topics of the text are presented in a logical, clear fashion. However, the chapter on “systems thinking” should appear first to provide foundational information on systems/General Systems Theory before moving into Industrial Engineering.

Interface rating: 5

The text is well crafted and is without significant interface issues. The chapters are accessible, and one is clearly able to view images and charts.

Grammatical Errors rating: 5

The textbook does not contain any significant grammar and syntax issues

Cultural Relevance rating: 5

The text is culturally insensitive and does not contain offensive language.

Reviewed by David Olawale, Assistant Professor, University of Indianapolis on 4/23/21

I like the key concepts covered. They are critical to an IE and can be covered within a semester-long course. I particularly like the order of the topics. read more

I like the key concepts covered. They are critical to an IE and can be covered within a semester-long course. I particularly like the order of the topics.

The contents are accurate and there is proper attribution to the sources of information.

The content is fundamental and will not easily become obsolete. The organization of content is such that it will be relatively easy to update.

The language and writing style is very easy for anyone (first-year college student) to understand.

Consistency rating: 4

It would have been nice if there was a short introduction at the beginning of each chapter.

The chapters are relatively short.

Organization/Structure/Flow rating: 5

Interface rating: 4

It worked well.

Grammatical Errors rating: 4

Pg 3 - Minor grammatical errors e.g. “Certain words are show…” instead of 'shown'. Little error under Safety and Work Environment section: “The system should be changed to eliminate or reduce the change of that type of accident occurring.”

It is not culturally insensitive.

It would have been nice if there was a short introduction at the beginning of each chapter. Exercise should include some quantitative problems e.g. chapter 5 on Models.

Table of Contents

• 1. What is Industrial Engineering?
• 2. Teamwork
• 3. What is Problem Solving?
• 4. Big Ideas in Industrial Engineering
• 5. Using Models
• 6. Deming's 14 Points
• 7. People in the System
• 8. Systems Thinking
• 9. Lean Operations
• 10. The IE Approach
• 11. Organizations' Missions, Visions, and Values
• 12. Lifelong Learning

Ancillary Material

About the book.

This book was created for an undergraduate Introduction to Industrial Engineering course at The University of Texas at Arlington (UTA).  The chapters give an overview of the profession and an introduction to some of the tools used by industrial engineers in industry.  There are interactive content exercises included at the end of most chapters.  This interactive content aims to engage students in the content as they are reading.  The book will continue to revised and updated with new information as it becomes necessary.

About the Contributors

Contribute to this page.

• Oct 13, 2019

10 Steps to Problem Solving for Engineers

Updated: Dec 6, 2020

With the official launch of the engineering book 10+1 Steps to Problem Solving: An Engineer's Guide it may be interesting to know that formalization of the concept began in episode 2 of the Engineering IRL Podcast back in July 2018.

As noted in the book remnants of the steps had existed throughout my career and in this episode I actually recorded the episode off the top of my head.

My goal was to help engineers build a practical approach to problem solving.

Have a listen.

Who can advise on the best approach to problem solving other than the professional problem solvers - Yes. I'm talking about being an Engineer.

There are 2 main trains of thought with Engineering work for non-engineers and that's trying to change the world with leading edge tech and innovations, or plain old boring math nerd type things.

Whilst, somewhat the case what this means is most content I read around Tech and Engineering are either super technical and (excruciatingly) detailed. OR really riff raff at the high level reveling at the possibilities of changing the world as we know it. And so what we end up with is a base (engineer only details) and the topping (media innovation coverage) but what about the meat? The contents?

There's a lot of beauty and interesting things there too. And what's the centrepiece? The common ground between all engineers? Problem solving.

The number one thing an Engineer does is problem solving. Now you may say, "hey, that's the same as my profession" - well this would be true for virtually every single profession on earth. This is not saying there isn't problem solving required in other professions. Some problems require very basic problem solving techniques such is used in every day life, but sometimes problems get more complicated, maybe they involve other parties, maybe its a specific quirk of the system in a specific scenario. One thing you learn in engineering is that not all problems are equal. These are

 The stages of problem solving like a pro:

Is the problem identified (no, really, are you actually asking the right question?)

Have you applied related troubleshooting step to above problem?

Have you applied basic troubleshooting steps (i.e. check if its plugged in, turned it on and off again, checked your basics)

Tried step 2 again? (Desperation seeps in, but check your bases)

Asked a colleague or someone else that may have dealt with your problem? (50/50 at this point)

Asked DR. Google (This is still ok)

Deployed RTFM protocol (Read the F***ing Manual - Engineers are notorious for not doing this)

Repeated tests, changing slight things, checking relation to time, or number of people, or location or environment (we are getting DEEP now)

Go to the bottom level, in networking this is packet sniffers to inspect packets, in systems this is taking systems apart and testing in isolation, in software this is checking if 1 equals 1, you are trying to prove basic human facts that everyone knows. If 1 is not equal to 1, you're in deep trouble.At this point you are at rebuild from scratch, re install, start again as your answer (extremely expensive, very rare)

And there you have it! Those are your levels of problem solving. As you go through each step, the more expensive the problem is. -- BUT WAIT. I picked something up along the way and this is where I typically thrive. Somewhere between problem solving step 8 and 10. 

The secret step

My recommendation at this point is to try tests that are seemingly unrelated to anything to do with the problem at all.Pull a random cable, test with a random system off/on, try it at a specific time of the day, try it specifically after restarting or replugging something in. Now, not completely random but within some sort of scope. These test are the ones that when someone is having a problem when you suggest they say "that shouldn't fix the problem, that shouldn't be related" and they are absolutely correct.But here's the thing -- at this stage they have already tried everything that SHOULD fix the problem. Now it's time for the hail mary's, the long shots, the clutching at straws. This method works wonders for many reasons. 1. You really are trying to try "anything" at this point.

2. Most of the time we may think we have problem solving step number 1 covered, but we really don't.

3. Triggering correlations.

This is important.

Triggering correlations

In a later post I will cover correlation vs causation, but for now understand that sometimes all you want to do is throw in new inputs to the system or problem you are solving in order to get clues or re identify problems or give new ways to approach earlier problem solving steps. There you have it. Problem solve like a ninja. Approach that extremely experienced and smart person what their problem and as they describe all the things they've tried, throw in a random thing they haven't tried. And when they say, well that shouldn't fix it, you ask them, well if you've exhausted everything that should  have worked, this is the time to try things that shouldn't. Either they will think of more tests they haven't considered so as to avoid doing your preposterous idea OR they try it and get a new clue to their problem. Heck, at worst they confirm that they do know SOMETHING about the system.

Go out and problem solve ! As always, thanks for reading and good luck with all of your side hustles.

If you prefer to listen to learn we got you covered with the Engineering IRL show!

For Youtube please go to:

https://youtu.be/EHaRNZhqmHA

For Spotify please go to:

https://open.spotify.com/show/3UZPfOvNwQkaCA1jLIOxp4

And don't forget to subscribe if you get any value from the Engineering IRL Content

• Technical Tactics
• 10+1 Steps to Problem Solving

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Book description

Industrial Problem Solving Simplified provides a roadmap for solving manufacturing problems. Containing numerous examples of actual problems and their solutions in various industrial environments, it is for novice as well as experienced manufacturing owners, managers, quality representatives, consultants, trainers, and procurement professionals.

Author Ralph Pawlak's roadmap is a proven system that has been used to eliminate major manufacturing problems in electronics, casting, blow molding, and assembly operations. What's more, it has been used effectively in the manufacture of toys, juvenile products, chemicals, automotive engines, and innumerable components of many manufacturing facilities—and in the U.S., Canada, China, and Europe. The book's insights into problem causes and the methods to solve them once and for all are applicable to most problems in most industries.

Pawlak, with decades of experience as manager of manufacturing, quality, and plant engineering for General Motors, Fisher Price, Vibratech, and others, offers tools to solve problems and shows how to use them. You'll learn how to use tools like quality check sheets, flow diagrams, concept sheets, duo diagrams, variation plots, sketches, sum-of-extremes tests, good versus bad comparisons, fractionals with interactions, and many-level checks. What's more, these are tools anyone can put to good use today . No special knowledge of statistics, or advanced math or engineering, is required. If you can add, subtract, multiply, and divide—and use your eyes and ears—you can learn to solve industrial problems like a pro.

This book will help you:

Clarify the conditions that cause problems

Define the cause of problems

Generate clues as to the causes of problems and their solutions

Collect accurate and relevant data

Use specific tools to solve problems effectively

Establish consistent work processes to ensure problems do not return

Industrial Problem Solving Simplified will empower you and your people not just to solve manufacturing problems but optimize processes, improve productivity, and save money. With the plans, examples, and worksheets in this book, you will become a proficient problem solver.

What you'll learn

How to determine problem causes

How to identify defects

How to manage the problem and its solution through data collection and clue generation

How to use simple analysis tools

How to establish a consistent work process to maintain improvements after the problem is solved

Who this book is for

Owners, managers, line workers, quality controllers, consultants, trainers, purchasing agents, and others in any company that has manufacturing facilities in house or outsourced.

Table of contents

• Apress Business: The Unbiased Source of Business Information
• About the Author
• Acknowledgments
• Introduction
• The Cause and Why It Is Important
• Problems: Inherent in Manufacturing
• Key to Gleaning Clues and Solving Problems
• Defects: Clues to a Problem’s Cause
• Start with Conditional Data
• Collect Quantifiable Data
• Enter the Concept Sheet
• Poor Fusion Weld Concept Sheet
• Front Cover Oil Leak Concept Sheet
• Leaks Concept Sheet
• Failure Concept Sheet
• Bent Ignition Coil Connector Pins
• A Focus on Process: Engine Assembly Routing
• PCB Board Process Map
• Use Your Concept Sheet
• A Simple Plan of Attack
• Evaluation Considerations
• Photographs of Seal Conditions
• Simple Tools Work Well
• Acceptable and Unacceptable Thrust Bearings
• Use the Problem Sheet to Gather Data
• Collect Variable Data
• Collecting Attribute Data
• Visual Evaluation System
• Define the Problem
• Verify the Process
• Develop an Assessment Plan
• Conduct Checks
• React to the Problem
• Example Manufacture Design
• Guidelines for Clue Collection
• Identify and Sequester Bad Parts
• Use a Defect Diagram
• Six Prime Problem-Solving Tools
• Basic Analysis
• Trait Peculiarities
• Sum of Extremes Test
• Comparison of Individuals in Duos (Sets of Two Units)
• Comparison of Individuals in Groups
• Group Data Applications
• Fractional Analysis
• Tests for Clue Generation or Verification
• Visual Observation
• Lot Identification Flowcharts
• Sound Problems
• Cracked or Broken Problem Sheet
• Consistent Work
• Many-Level Reviews
• Certify Problem Solutions and Verify
• Case Study: The Value of Comparisons
• CHAPTER 10: Summary
• APPENDIX A: Fractional Explained
• Stuffing Example
• Stripped-Threads Example
• Balance Shaft Assembly Noise
• APPENDIX C: Cracked-or-Broken Example
• APPENDIX D: Torque-to-Turn Example
• APPENDIX E: Sum of Extremes Test
• APPENDIX F: Definitions

Product information

• Title: Industrial Problem Solving Simplified: An 8-Step Program
• Release date: January 2014
• Publisher(s): Apress
• ISBN: 9781430265771

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Problem Solving Techniques for Process Industry Professionals

Problem solving and decision making are key facets of any successful operation. Engineers are blessed with typically excellent logic skills. But sometimes these innate skills require channeling; especially when working through problems with a team of colleagues. So PIF has looked at five problem solving solutions that will take your decision making to the next level.

5-Why Problem Solving Technique

The 5-Why Problem Solving technique is said to have been popularised in the 1970s by the Toyota Production System. “When you have a problem, go to the place where the problem occurred and ask the question 'Why' five times,” say Reliable Plant . “In this way, you will find the root causes of the problem and you can start treating them and rectifying the problem.”

It's a good tool to start your problem solving process but often requires additional follow-on methods. Mind Tools add, “The 5 Whys strategy is an easy and often-effective tool for uncovering the root of a problem. Because it's simple, you can adapt it quickly and apply it to almost any problem. Bear in mind, however, that if it doesn't prompt an intuitive answer, you may need to apply other problem-solving techniques.”

Ishikawa Diagram

The Ishikawa Diagram – also known as the Fishbone or Cause and Effect Diagram – is a graphical aid to determine the relationship between a problem and its potential causes.

Reliable Plant say, “One of the most effective ways of constructing such a diagram is to brainstorm potential causes in a team environment. For example, a cause and effect diagram might be used to determine possible causes of a recurring defect in a manufacturing process.”

The diagram resembles the skeleton of a fish, with the problem on the right side. They continue, “The major cause categories are written in the boxes on the left side of Cause and Effect Diagram. Summarize the major causes under the categories. These categories are usually Methods, Measurements, Machines, Materials and People.”

Plan, Do, Check, Act (PDCA)

The Plan-Do-Check-Act (PDCA) Cycle ensures that ideas are appropriately tested before committing to full implementation. “It begins with a Planning phase in which the problem is clearly identified and understood,” say Mind Tools.

“Potential solutions are then generated and tested on a small scale in the 'Do' phase, and the outcome of this testing is evaluated during the Check phase. 'Do' and 'Check' phases can be iterated as many times as is necessary before the full, polished solution is implemented in the 'Act' phase,” they add.

Simplified Failure Modes and Effects Analysis

Simplified Failure Modes and Effects Analysis (SFMEA) is a recognised industry approach for top-down analysis of a design. According to Reliable Plant, “You start by considering each component or functional block in the system and how it can fail, referred to as failure modes. You then determine the effect of each failure mode, and the severity on the function of the system.

“Then you determine the likelihood of occurrence and of detecting the failure. The procedure is to calculate the Risk Priority Number, or RPN, using the formula:
RPN = Severity × Occurrence × Detection.” It's then a case of figuring out corrective actions to either reduce occurrence or increase detection and ultimately bring down the RPN as low as possible.

These four tools, when allied with common sense and logic, can be be a potent force for change when your team is dealing with any manner of problem solving situations that can crop up on a daily basis. Visit Reliable Plant or Mind Tools for more ideas.

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8 Systems Thinking

Chapter table of contents, system definition, system analysis, system properties and archetypes, systems thinking.

The educational system in the US has these parts:

• Preschool and kindergarten,
• Elementary schools – grades 1-6,
• Middle schools – grades 7-8,
• High schools – grades 9-12, and
• Higher education, including 2-year community colleges, and 4-year colleges and universities.

We call this list of parts a “system” because the parts interact with each other to achieve overall goals, such as an educated population. The parts may interact through cause and effect or through the exchange of information or material. We can think of the input and output of the overall system, and we can also think about the input and output of each part; for example, some of the students who graduate from middle school (an output) go on to high school (an input). We can also think of the parts as being processes in the educational system.

In his book, Total Quality Control [1] , Feigenbaum defines a system as:

A group or work pattern of interacting human and machine activities, directed by information, which operate on and/or direct material, information, energy, and/or humans to achieve a common specific purpose or objective.

Clearly this definition relates closely to industrial engineering and explains why some industrial engineering departments are called industrial and systems engineering. UTA’s department is called Industrial, Manufacturing, and Systems Engineering. However, systems engineering is also used sometimes in a more limited meaning, to refer to designing a computer and information system.

When we define a system we implicitly draw a line around some parts to include those parts and to exclude others. For example, the educational system includes the schools, but not the roads students travel on to get to school or the organizations that employ students after they graduate. Generally, looking at a larger system is more accurate but harder. We can understand some aspects of the educational system without considering these other parts, but some aspects require looking at the larger system. We can still examine the educational system if we remember to include in our study its interactions with its environment, such as the transportation system and the employment system.

For the IE, the systems approach is important because it reminds us to consider the environment surrounding the system we are studying and to move the boundaries outward as much as possible so that we consider a problem in its larger context.

Some systems have feedback . Feedback in a system is when outputs are fed back in as inputs for future system action.  This is sometimes called a feedback loop .  The educational system doesn’t tend to have a lot of feedback and that may hamper improvement of the system. Have you ever been asked by your high school to give feedback on how well your education prepared you for college or for work?

The operation of a system that has evolved without conscious design or a system that has been designed piece by piece almost always can be improved. Analysis means to take a system apart in order to understand how the parts work; systems thinking stresses synthesis , that is, understanding how the parts work together and how the system works as a whole. Understanding how each part of the educational system works is not enough for a good understanding and certainly not enough for making recommendations for improving the educational system; better recommendations would come from understanding how the parts of the system work together also.

A system has the property that a change to one part can have effects, sometimes surprising effects, on other parts. A state might require that students entering state-funded four year universities meet certain standards (for example, knowledge of a foreign language). The effects of such a change might be good for the universities, but the effects on the high schools must also be considered; they might, for example, have to provide more language classes and hire more teachers. Improving one part of system may have good or bad consequences on another part of the system. Using antibiotics to cure diseases has had the consequence of creating bacteria that are immune to some antibiotics; within the system of individual patient and doctor, having the patient take antibiotics makes sense, but in the larger system, we might want to be more cautious about their use.

A system may have emergent properties , that is, properties of the whole that are not the property of any part. For example, living systems are alive, but one can’t isolate that property in any part of the system; it is a property of the entire system.

A system can further be classified in these ways:

• Natural (for example, a river) or man-made (for example, a bridge),
• Static (for example, a bridge) or dynamic (for example, the U.S. economy),
• Physical (for example, a factory) or abstract (for example, the architect’s drawing of the factory), and
• Open (interacting with its environment) or closed (interacting very little with its environment)

Certain types of systems with feedback occur frequently in organizations and in society. If you learn to recognize them, you can learn what actions to take. William Braun describes 10 system archetypes :

• Limits to Growth (aka Limits to Success)
• Shifting the Burden
• Eroding Goals
• Success to the Successful
• Tragedy of the Commons
• Fixes that Fail
• Growth and Underinvestment
• Accidental Adversaries
• Attractiveness Principle

This article, Interaction Structures of the Universe , has a summary of the above models.

In this book The Fifth Discipline [2] , Peter Senge argues that organizations must become learning organizations by building knowledge of four disciplines: personal mastery, mental models, shared vision, and team learning. The “fifth discipline” is systems thinking, and he gives these laws of complex systems :

•  “Today’s problems comes from yesterday’s ‘solutions.'” Solutions can have unintended and undesired effects.
• “The harder you push, the harder the system pushed back.” “Compensating feedback” may keep a system in the state it started.
• “Behavior grows better before it grows worse.” Actions that make short term improvement may cause long term disaster.
• “The easy way out usually leads back in.” Easy and obvious solutions would have been done already if they would have worked. Hard work is needed to find the real solution.
• “The cure can be worse than the disease.” Some easy solutions become addictive.
• “Faster is slower.” Any organization has an optimal rate of growth.
• “Cause and effect are not closely related in time and space.”
• “Small changes can produce big results – but the areas of highest leverage are often the least obvious.”
• “You can have your cake and eat it too – but not at once.” For example, an improvement in quality pays off eventually in improved profits.
• “Dividing an elephant in half does not produce two small elephants.” Some problems must be solved by improving the whole system.
• “There is no blame.” “You and the cause of your problems are part of a single system.”

While most engineers design physical objects (cars, bridges, and so forth), IEs design and improve production systems. A production system is a system that produces goods or services for customers. IEs have to think about how a production system works as a system by using the types of ideas I’ve just described.

Choose one of the Laws of Complex Systems which you’ve seen demonstrated in your life.  Identify the law you’ve chosen and describe the “real-world” example of it in action which you’ve seen.  Your instructor may ask you to submit your answer.

• Feigenbaum, A. V. (1961). Total Quality Control. New York: McGraw-Hill. ↵
• Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. New York: Doubleday/Currency. ↵

Introduction to Industrial Engineering Copyright © 2020 by Bonnie Boardman is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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H. Milton Stewart School of Industrial and Systems Engineering

College of engineering, undergraduate.

The Stewart School of Industrial and Systems Engineering’s (ISyE) undergraduate program has been ranked the #1 program of its kind in the nation since 1991 according to the U.S. News & World Reports. While many of our students seek out our program because of our top rankings, they are equally attracted to the number of concentrations and academic interests offered. Yet one of the most alluring qualities of this program is the flexibility of career options that our Bachelor of Science (BSIE) degree allows.

Bachelor of Science in Industrial Engineering

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• Advanced Studies for Operations Research and Statistics
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At ISyE, we work on ways to improve a variety of complex systems by formulating and analyzing abstract models in search of making systems more efficient and optimizing performance. We address how people and the decisions they make contribute to the complexity of systems and how people benefit when those systems are analyzed. We immerse ourselves in the depth and breadth of decision-based technical problem solving by focusing on the disciplines of industrial engineering, operations research, and systems engineering. So, what does that all mean?

Problems Industrial Engineer's Solve

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Why choose ISyE at Georgia Tech?

The ISyE undergraduate program has been ranked the No. 1 of its kind in the nation since 1991, according to U.S. News & World Reports. While many of our students seek out our program for that reason, they are equally attracted to the breadth of study. Our BSIE curriculum provides the technical expertise one would expect in an engineering major, as well as excellent preparation to function in a wide range of professional settings like manufacturing, logistics, economic and financial modeling, transportation, consulting, health and humanitarian logistics, and more. Our undergraduates move on to distinguished careers in dozens of fields. The median starting salary with a B.S. in Industrial Engineering is $74,000.

As practitioners and researchers in industrial engineering, operations research, and systems engineering, we are technical problem solvers.

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• Bain & Company
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• Boston Consulting Group
• Capital One
• Caterpillar
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• Check Point Software Technologies
• Chick-Fil-A
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• The Home Depot
• Kimberly-Clark
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Prospective undergraduate students are highly encouraged to attend a campus tour and admission information session provided by the Office for Undergraduate Admission .

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VCU College of Engineering News

From infant care and virtual reality to art preservation and submarines, VCU Engineering students show off their creative problem-solving

Winners of College of Engineering’s annual Capstone Design Expo reflect dedication across an array of disciplines.

By Leila Ugincius

For the past year, seniors in Virginia Commonwealth University’s  College of Engineering  have been working to make the world a better place for humankind.

Whether assembling a wheelchair-lifting system, constructing a hybrid bike for veterans with limited mobility or exploring safe human-industrial robot collaboration, the senior class unveiled their research projects on April 26 at the college’s annual  Capstone Design Expo .

A signature event of the college, the expo represents the culmination of the graduating class’s education and showcases their innovative research and design prototypes from their yearlong senior Capstone Design course. The required class teaches leadership, teamwork and design skills.

Faced with challenges when developing prototypes, students gain valuable insights into the intricacies of designing innovative solutions. For many, the process highlights the importance of flexibility and adaptability in problem-solving.

The long-term nature of the projects sets this course apart from the rest of the curriculum. Students discovered the challenges of turning their initial ideas into a functioning product – and that building a solution is far tougher than designing it.

Here are summaries of the 2024 Engineering Capstone Design Expo winners.

BIOMEDICAL ENGINEERING

Mini Sensors to Track Movement of Preterm Babies  (BE 24-103)

Ashlyn Jones, Ireleigh O’Malley, Sarah Johnson, Adriana Bautista and Ishika Singh (advisor: Thea Pepperl)

“Premies” — babies born prematurely — are more susceptible to health challenges and require constant monitoring. This project tracks newborns’ movements using sensors to identify any potential issues, such as neurological complications or infections. It aids in early detection, ensuring these babies receive care for optimal health and development.

“We faced challenges when prototyping and choosing the most suitable wearable design to meet our sponsor’s specifications, since we needed to ensure the sensor was protected, the device as a whole could be sterilized, and maximized the baby’s comfort,” Bautista said.

CHEMICAL AND LIFE SCIENCE ENGINEERING

Subcritical Hydrothermal Catalytic Degradation of PFAS  (CLSE 24-204)

Abdullah Alqallaf, Jazzamine Threatt, Holly Sheppard and Anthony Anzelmo (advisor: Frank Gupton)

Poly- and perfluoroalkyl substances — commonly referred to as PFAS, or “forever chemicals” — take nearly forever to breakdown and, since they contaminate drinking water, can build up in the body over time. Forever chemicals are used to create common household products such as cleaning solutions, nonstick cookware and personal care items, and demand to find ways to break down PFAS is steadily increasing every year.

This project developed a continuous method of degrading PFAS found in water. Implementing two separate methods, the students removed up to 76.5% and 98.8% total PFAS, respectively, setting the stage for future experiments to see how adsorption affects the final concentration of PFAS in the treated solution.

COMPUTER SCIENCE

Sentiment Voice: Integrating Emotion AI and VR Performance in Arts  (CS 24-319)

Josiah Wilson, Chase Taylor and Ariana Thomas (advisor: Alberto Cano)

Can artificial intelligence “read” people’s emotions when they’re inside virtual reality? The students developed a system using the Unity Platform that tracks a user’s emotional changes.

Based on what users say and how their facial expressions change, the environment — in this case, a computer-generated Tokyo — changes around them, showing how someone’s emotions can project into the environment around them.

Based on research by VCU’s Semi Ryu, Ph.D., the project offers potential in multiple settings, including treating patients with PTSD or helping users process trauma and stressful situations.

ELECTRICAL AND COMPUTER ENGINEERING

Microgrid Model and Design  (ECE 24-405)

Madison Hofmann, Steven Holt, Amanda Orndorff and Jalen Richardson (advisor: Zhifang Wang)

Dominion Energy sponsored this project, in which the students designed an energy management system — essentially, a tiny computer controller that functions as a brain — to forecast electric demand. The “brain” helps decide how to use electricity most efficiently and at the best price by determining where the electricity should come from — the sun, the wind or a diesel generator.

As the world continues to shift toward renewable energy, the students wanted to think small (as in, microgrids) as well as big.

“Since microgrids rely on small, local generation, this makes them optimal for deploying renewable energy resources,” Holt said. “Implementing renewable energy throughout communities using wind turbines, rooftop solar panels and even solar carports reduces the need for large power farms that consume large amounts of land. Having power available locally also reduces stress on long-distance transmission networks and increases reliability in times of high grid instability. Ultimately, microgrids are an efficient way of implementing a sustainable, renewably powered future.”

MECHANICAL AND NUCLEAR ENGINEERING

Fabrication of Magnetic Filaments for Fused Deposition Modeling Technology  (MNE 24-503)

Thomas Pierce, Micaiah Akyeampong, Vincent Mazzochette and Kamau Bey (adviser: Radhika Barua)

Additive manufacturing — building something by adding material one layer at a time — reduces reliance on traditional supply chains by enabling on-demand production of spare parts and components.

One of the most common methods of additive manufacturing is fused deposition modeling, better known as 3D printing, which extrudes a plastic filament in a series of layers to create the 3D object.

This team set out to produce a magnetized filament by combining recyclable polymer with magnetic powders and conductive fillers. Ultimately, the proposed filament could be used for 3D-printing electromagnetic shielding, which is used for applications such as surface ship radar, weather radar, air traffic control, inflight Wi-Fi and spacecraft telemetry.

MULTIDISCIPLINARY

VMFA Horizontal Track System  (MULTI 24-618)

Cole Jordan, Zach Mazzola, Andrew Shalaski and Matthew Hayden (advisers: Reza Mohammadi, Dan Resler)

Art conservationists meticulously preserve and repair paintings that tie us to the past by using fine precision tools, including microscopes. But the risks – even just a minuscule flake of paint chipping off during movement or inspection – are high.

This group set out to design a track system to allow a microscope to travel over large pieces of art. Think of a claw machine at the arcade, where the claw can be positioned and then lowered – though in this case, the “prize” isn’t touched.

The current industry standard for such inspection costs hundreds of thousands of dollars. This system can be built in stages, starting with manual motion based on a system of rails and carriages — like a drawer — that can then be upgraded to automated motion with motors. It can be installed for about $8,500.

BEST INDUSTRIAL

Advanced Rudder Actuation  (MNE 24-509)

Keely Cooley, Alex Sellers, Thomas Goldstein and Daniel Woodworth (adviser: Worth Longest)

Few modifications have been made to control systems in submarines over the past century, with new technologies having issues of scalability and cost. The team wanted to explore better maneuverability, stealth and efficiency of submarines.

After creating more than 15 novel rudder and control designs, the team chose the top three for further analysis: a whale-inspired tubercle design, a triple-hinged flap and a compliant mechanism design. The students then prototyped and tested each design in a wind tunnel, comparing the results with a control test sample and to each other. The major measures of success were maximum lift-to-drag ratios of hydrofoils, minimal acoustic effects and signatures, and robustness of the design.

Preliminary results showed that while the whale tubercle design acted as intended, a few changes to the design could have increased the lift-to-drag ratio in comparison with the control sample. Analysis is still underway for the compliant and segmented hydrofoils, which are expected to perform better than the tubercle design.

EXCELLENCE IN DESIGN

Design to Reduce Pulse Oximeter Reading Inaccuracies Due to Skin Pigmentation  (BME 24-107)

Jayla Johnson, Ellen Patchin and Mariana Fernandes Gragnani (adviser: Barbara Boyan)

Patients of color often receive delayed oxygen treatment due to inaccuracy in readings from the pulse oximeter — the device that clips on to a finger to measure oxygen in blood. Current models report a larger number than usual, which can be dangerous as doctors don’t realize the patient actually needs more oxygen.

The students developed a new oximeter that improves how it measures the oxygen in blood, regardless of skin color.

“Health care has a long history of racial and gender-related disparities that have long affected the quality of treatment many individuals receive,” Pathcin said. “This has taken the form of issues like the one our project addresses, where the technology itself is not suited for darker skin tones, and medical practices founded on misinformation and medical myths.”

PEOPLE’S CHOICE

Formula SAE Aerodynamic Front Wing Design  (MNE 24-516)

Carson Clark, Jonathan Morton, Garrett Giddings and Ryan Noll (advisers: Bradley Nichols, Laleh Golshahi)

Ram Racing, the multidisciplinary student organization that designs, builds and races Formula 1, Formula E and Mini Baja race cars from scratch, wanted to improve the performance of its next race car.

Members of this project group who have experience racing the car have noticed a serious performance problem when the car enters a corner. The car lacks traction at the front wheels and slides, rather than turns, when cornering, which slows its speed in that part of the racecourse.

Speaking to other FSAE race teams from other Virginian colleges, the Capstone team learned that many race teams have little to no background research or analysis for their front wing design. The student team designed a two-foil front splitter for a Formula SAE car to produce maximum downforce while maintaining laminar flow over the front tires.

“It’s the opposite of an airplane wing,” Noll said. “Instead of lifting the plane up, it forces the car down.”