PROBLEMS ARE THE GOLDEN EGGS problems??? day by day in our proffessional life we faces so many problems, but didn't recognize about the problem. Because we are habituate to facing to problems, if we want to solve the problems, first we can feel YES am facing a problem then you have a chance to solve it... after that we should find is it REPEATATIVE problem or New problem, on the bases of the issue we can take further steps, how to break it. how to analyse, how to find countermeasure, how to check is it suitable or not, how to make standard

1. PROBLEM SOLVING
PRESENTED BY
SURESH NAIDU. B

2. What is a Problem?
“A doubtful or difficult matter requiring a solution”
and
“Something hard to understand or accomplish or deal with.”
Definition
A systematic approach to defining the problem (question or situation
that presents uncertainty, perplexity or difficulty) and creating a vast number
of possible solutions without judging these solutions.

3.  It begins with the general identification of a large issue within the plant. The next several
steps work to clarify the nature of the problem itself, and then perform root cause
analysis to identify the reasons the problem is happening.
 At this point, solutions are identified and put in place, then evaluated and standardized.
 Solving the problem would then be clarifying the nature of the downtime, measuring the
amount of downtime is being experienced, and locating the point of cause in the
process that is failing.
 The team would then perform a “5 Why” root cause analysis and determine
countermeasures to eliminate the root causes of failure.
 They would then evaluate the performance after the fixes to see if they had the desired
impact. At that point the fixes would become part of the standard work for that process
and potentially be replicated to other areas of the plant, where applicable.

4. Steps in the Problem-Solving Process
we will look at the steps in a typical problem-solving process and how those
can be impacted by smart manufacturing solutions.
1. Initial Identification of Problem
2. Form Team
3. Clarify & Describe Problem
4. Root Cause Analysis / 5 why’s
5. Create solutions
6. Test the solutions
7. Measure and Analyze results
8. Standardize the solution

6.  Historical performance information that captures production rates, uptime & downtime
information, quality data and much more
 Detailed process data showing pressures, temperatures, PLC data, etc
 Who was running the process, what was being manufactured, time of day, day of week
 Well-designed workflows that help users through the problem-solving steps
 Structured communication platforms that keep the team on the same page and
facilitates group productivity

7. Step 1: Initial Identification of
Problems
 On any manufacturing floor I’ve ever
been to, there has never been a lack
of issues to be addressed. There are
always problems to fix, processes to
improve, and so forth.
 The historical performance
information shows exactly how big
each problem is, how they are
trending, and more
 This helps to determine which should
be the highest priority issues to work
on

8. Step 2: Form the Team
 Once it is decided which problem is going to be addressed, a team must
be assembled.
 Well-designed workflows help users through the problem-solving steps,
showing the relevant information at each step, tracking inputs from
multiple users, and consolidating information in a single platform. Most
projects today have information spread through multiple systems and,
even more, in multiple excel spreadsheets that have access and version
control issues. All that can be eliminated.
 Structured communication platforms that keep the team on the same page
and facilitates group productivity. In addition, modern platforms facilitate
communication by integrating tools like Microsoft Teams or Slack. Instead
of having communication happening across multiple emails and
spreadsheets, communication can be facilitated right into the workflow
and analysis platform.

9. Step 3: Clarify and Describe the
Problem
 One of the key benefits to these systems is the contextual
information captured for each one of these events: Who
was running the process, what was being manufactured,
time of day, day of week
 One of the most basic methods of finding the cause of
problems is to ask the five different “W” questions (plus
one “H”).
 This method can be very beneficial if done correctly. For
example, if you are preparing to create charts of possible
causes or perform a statistical analysis, this method can
help you identify possible causal factors.
 It can be used as a brainstorming tool

10.  For example, it is not enough to know that my first pass yield went from
97% to 93%.
 on *how* the part failed the test. The systems can know *who* is logged
into the stations. By knowing what machines were used for which parts,
the system can know *where* the problem occurred.
 They will also know *when* that defect occurred. Finally, by tracking the
detailed process variables as the part was processed, the system can track
*what* happened during the production.

11. Step 4: Contain the problem
 By understanding what things are contributing to the problem, we are now
in a position to implement a short-term fix. While we should not be
satisfied with putting a Band-Aid on the problem, this can contain quality
or safety issues while a permanent fix is sought.
 Having a good analysis prior to this point will help determine the proper
containment measure to implement.

12. Step 5: Root Cause Analysis
 Graphical Evaluation – In this method, data about the progress
is put into graphical form where the users can evaluate it
visually. At Visual Decisions, we are big fans of this type of
analysis! Smart manufacturing systems are fantastic for this
type of analysis. Because they are so data rich, most of the
information you’d like to know about the process can be
charted and shared for analysis.
 FMEA – In another webinar, I’ve discussed how to create an
“ever-green” FMEA (failure mode and effect analysis) that is
continually updated with information from the shop floor.
Based on the symptoms observed on the shop floor, this tool
can be used to see if there are known causes for failure to
investigate.

13.  The most common type of root cause analysis done in
lean manufacturing environments is 5 Why analysis.
 In this method, we keep asking why until we get down
to the root cause for the problem.

14.  In this method, you show the problem (or effect) to the right
side of the diagram (shown in the triangle on the right side
in the inset picture).
 Then you try to determine all the contributing factors to the
problem.
 It is typical (but not required) that the first “branches” in the
analysis are man, machine, material, method, management,
and environment.
 Then you ask what it is that is causing the issue.

15. Statistical Analysis of Factors
 Finally, we close out this section with a brief discussion of the
gold standard of data-based root cause analysis. Some of the
forms of statistical analysis that apply here are:
1. Analysis of Variance (ANOVA)
2. Design of Experiments (DOE)
3. Linear and Multiple Regression
4. T-Tests
5. Chi-Square tests
These methods are at the heart of Six Sigma analysis.
Obviously, these methods are also very heavily dependent on
data. The more data, the better. The richer and more
contextualized that data can be, the better these methods will
work.

16. Step 6: Create Solutions
 Another big impact of Industry 4.0 is to broaden the solution space. For
many problems in manufacturing, the fix will be some alteration to the
physical equipment involved. Going back to the fishbone diagram, these
fixes primarily relate to the “Machine” branch. However, when the problem
is related to Man, Material, Method, Management or Environmental the fix
is often process or system based.
 Many times the problem can be traced back to a lack of standard work or a
lack of adherence to the standard work.
 In many quality-related problem-solving efforts, technology can be a key
part of error-proofing, automated inspection, and other solutions.

17. Step 7: Testing the Chosen Solution or Solutions
 A large portion of what we work on at Visual Decisions is
implementing I-IoT solutions within our customers.
 These platforms have tremendous flexibility to address
common (and uncommon!) issues in manufacturing.
 Augmented and Virtual Reality. Not only can these
technologies be a solution to many manufacturing issues,
but they can also be used to test out a wide variety of
other solutions.
 They can be used to give insight on how workers may
interact with those potential solutions before making
heavy capital investments putting them into place.

18. Step 8: Measure and Analyze the Results
 This is yet another place within the problem-solving process that acquiring and
analyzing data is crucial.
 In particular, having a system to collect the data 24/7 in an unbiased fashion is
critical. Because of the bias and inaccuracy inherent in manually collected data,
measuring the success of the solution in that fashion will lead to poor results.
 Another approach is to augment the data collection capabilities of the MES with an
IOT platform to handle some of those edge cases.
 This will make it a better and better fit, as opposed to a more monolithic solution.
 One of the dangers of using technology to solve issues is the creation of
“monuments”. In lean manufacturing, a monument is something that cannot be
moved or changed.

19. Step 9: Standardize the Solution
 When we think about standard work in manufacturing, the first thing
that pops into mind is getting all the operators to work with the
equipment in the same way every time.
 And absolutely that is part of the solution to many problems.
 Setting the culture and making a solution part of the process means
having the team leaders, supervisors, value stream managers and
executives all be a part of the solution.
 This solution not only showed the current values of all the KPI, but also
tied into all the improvement process being run across the sites.
 Because he used that to drive communication with his plant managers
every week, that put the pressure on them to understand the
information in that application to ensure the accuracy and
completeness.
 In turn, by using the solution in their meetings with their value stream
managers, they ensured the value stream leaders used that solution as
part of their daily and weekly processes.
 That emphasis made the solution part of the standard work that
happens on the shop floor shift by shift, day by day, and week by
week.

20. Closing thoughts
 Data is absolutely critical to identifying the improvement opportunities, analyzing
causal factors, generating solutions and more.
 Finally, when developing solutions on platforms such as I-IoT, use agile concepts to
implement incremental improvements and test those solutions when reaching the
minimal viable product stage of development.

21. What Skills do you use in Problem Solving
 Creativity. Problems are usually solved either intuitively or systematically. Intuition is used when no new
knowledge is needed - you know enough to be able to make a quick decision and solve the problem, or
you use common sense or experience to solve the problem. More complex problems or problems that
you have not experienced before will likely require a more systematic and logical approach to solve, and
for these you will need to use creative thinking.
 Researching Skills. Defining and solving problems often requires you to do some research: this may be
a simple Google search or a more rigorous research project.
 Team Working. Many problems are best defined and solved with the input of other people. Team
working may sound like a 'work thing' but it is just as important at home and school as well as in the
workplace.
 Emotional Intelligence. It is worth considering the impact that a problem and/or its solution has on
you and other people. Emotional intelligence, the ability to recognize the emotions of yourself and
others, will help guide you to an appropriate solution.
 Risk Management. Solving a problem involves a certain amount of risk - this risk needs to be weighed
up against not solving the problem.
 Decision Making. Problem solving and decision making are closely related skills, and making a decision
is an important part of the problem solving process as you will often be faced with various options and
alternatives.