Algorithmic Method of Problem Solving in the Engineering Conceptual Design

Zbigniew M. Bzymek,

Research Professor, Ph.D., zbigniew.bzymek@uconn.edu,

University of Connecticut, Storrs, Connecticut, USA

On the basis of the academic experience a teaching method for problem solving in conceptual engineering design is being developed. It is expected that it would meet the challenge of ongoing design research and would be an effective tool providing support for the most difficult phase of design – solving problems with contradictions. The Brief Theory of Inventive Problem Solving (BTIPS), that was compiled and developed in research done at the University of Connecticut, may be a prospective tool for performing such a task. Derived from TSIP and TIPS – BTIPS slightly differs from those methods. Modules Principles, Effects and Prediction introduced by IM, in BTIPS are reinforced and enhanced to meet the newest challenges of engineering pedagogy and technology. To meet those challenges principles of Size Reduction, Miniaturization, Nanotechnology and Biotechnology were introduced. The technological effects were enriched with new developments based on miniaturization, nanotechnology and biotechnology. Furthermore the application of Virtual Elements in the Prediction module were proposed to safe achievements of the current design process. The tests of functions' separation and minimum information content to evaluate the derived End Solution as well as several other tests are also the new recommendations. BTIPS is living, still developing and tested. It is taught and used, and constantly improving. This paper summarizes the method, its latest enhancements and shows ways of its applications. Key words: engineering design, problem solving, design principles, technological effects, designed system, preliminary solution, end solution, trimming, ideal solution.

Nomenclature

Acronyms, names and abbreviations:

· BTIPS: Brief Theory of Inventive Problem Solving - the theory compiled and developed from TRIZ, TSIP and TIPS at the University of Connecticut, USA;

· BS: Brain Storming - a method of idea generation introduced by Alex Faickney Osborn in 1961 and based on the Sigmund Freud’s theory of subconscious;

· IM: Invention Machine^TM - a problem solving software developed in the late 1980s and the 1990s by the Invention Machine^TM Corporation based in Minsk, Belarus and in Boston, Massachusetts, USA;

· IHS Inc.: Information Handling Services Incorporated - the US company based in Douglas County, Colorado that acquired Invention Machine^TM Inc. on 7^th of November 2012;

· TechOptimizer: Improved edition of Invention Machine^TM software;

· GoldFire: A problem solving software supporting optimization and innovation processes to enhance productivity - developed on the basis of Invention Machine^TM software, presently being distributed by IHS Inc.;

· TRIZ: Teoriya Resheniya Isobretatielskich Zadatsh (Russian: теория решения изобретательских задач – pronounce: teoriya resheniya izobretatielskikh zadatch) - Theory of Solving Inventive Tasks introduced by Genrich Saulovich Altshuller in 1946;

· TSIP: Theory of Solving of Inventive Problems, the name for TRIZ introduced in the book: Creativity as an Exact Science by G. S. Altshuller - translated from Russian by Anthony Williams (1984);

· TIPS: Theory of Inventive Problem Solving - the name derived from TSIP and introduced by the Invention Machine™ Corporation research team under leadership of Valery Tsourikov;

· ES: End Solution – in BTIPS problem solving procedure, the solution found at the end of the process that resolves the contradictions, solves the problem and performs the desired function;

· IS: Ideal Solution - in BTIPS problem solving procedure, the solution that satisfies the problem statement, solves the contradictions, requires minimum information to be described, takes minimum energy to function and fulfils other requirements of IS tests;

· PIS: Practical Ideal Solution - in BTIPS problem solving procedure, the IS that satisfies the conditions of feasibility, local application, economy or sometimes even requirements of political and social correctness;

· PrS: Preliminary Solution – in BTIPS module Principles, a solution to start the problem solving procedure that should solve the immediate problem even if creating another secondary problem;

· IF: Improving Feature - in BTIPS Principles module, the intermediate solution aspect that if considered, is bringing the process closer to the ES;

· WF: Worsening Feature - in BTIPS Principles module, the intermediate solution aspect that if applied, is pushing the solution process away from the desired ES;

· DS: Designed System - in BTIPS Prediction module, the system under design;

· PC – Physical Component - in BTIPS Prediction module, the Designed System (DS) the component that has physical representation and performs the required function;

· VE - Virtual Element - in BTIPS Prediction module, the element that performs the desired function but has no physical representation ;

· VS - Virtual System - in BTIPS Prediction module, the Designed System (DS) that contains virtual elements;

· VC - Virtual Component - in BTIPS Prediction module, the component of the Virtual System (VS) that has no physical representation but performs the required function.

Introduction

In the fast growing world of competing economies the industrial production plays the key role. The only chance for the advanced nations to maintain their leading economy position is to properly invest into technology and education. This could help them to retain their position which, according to some predictions may change after 2035 [1]. Engineering is a major part of industrial potential and design is a decisive part of engineering. The way of thinking is a derivative of culture and reflects every activity of the society. The engineering design and problem solving in particular, very much depends on ways of thinking.

Fig. 1 Structure of thinking processes [15] and the Algorithmic problem solving methods developed from Altsuller’s theory of problem solving

The methods of thinking (Figure 1) are describing procedures of rational decisions in domains of human activities. Problem solving process is one of those domains. In economy and technology the methods of problem solving have particular significance. In the last century two main approaches to problem solving were developed, psychological and algorithmic. The most significant among the psychological approach is Osborn’s proposal of Brain Storming based on Sigmund Freud’s theory of subconscious [2]. One of the most significant among algorithmic approaches is Altshuller’s method of problem solving. The Altshuller’s method [3] has established a very useful procedure of problem solving. Nam Suh’s [4] and Stuart Pugh’s [5] contributions brought however some aspects not considered by Altshuller. The algorithmic problem solving method introduced by Altshuller [3] and the researchers following him [6], [7] is a specialized tool for the engineering conceptual design. It was developed into several mutations. Known commonly as TRIZ was developed further as TIPS (Table 1). It was formalized in the IM^TM computer program packages [8], [9], [10] and [11]. It was further changed, abbreviated and equipped with additions at the University of Connecticut and named BTIPS [12], [13]. While BTIPS was developed mainly for teaching purposes, it still maintains its ability to be effective tool when used in practical engineering design and practice.

Modules of BTIPS have been re-defined and described [12], [13], [14], and [15]. To formulate the method more clearly the vocabulary of key words, a glossary of basic terms and definitions, algorithms and formulas, theorems and corollaries have been stated.

1. Some characteristics of TRIZ, TIPS and BTIPS

BTIPS is derived from TRIZ and TIPS. The developments of BTIPS: new principles, attributes and approaches, components and their interactions as well as physical and virtual elements are listed in Table 1.

Table 1

TRIZ, TIPS, BTIPS - Similarities and Differences [15]

The Method :	TRIZ	TIPS	BTIPS
Number of Principles :	40	40	44
Number of Features	36	36	40
Number of Effects	36	76	80
System Components	Supersystem, sytems, sub-systems	Supersystem, sytems, sub-systems	Super-system, systems, sub-systems, elements, items
Number of modules number	3	3	3
Algorythm	ASIP	TIPS Algorithm	Algorithm of Ideal Solution Search
Basic Theorem I	Not stated explicitely	Not stated explicitely	1.Minimum Energy of Ideal System
Corollaries derived from the Basic Theorem I	Not stated explicitely	Not stated explicitely	1.1The Ideal System has to solve the Basic Contradiction; 1.2. The Ideal System can’t be trimmed
Basic Theorem I I	Not stated explicitely	Not stated explicitely	2. Information needed to describe the Ideal System should be minimum
Corollaries derived from the Basic Theorem I I	Not stated explicitely	Not stated explicitely	2.1 Description of the Ideal System which does not contain redundant information can’t be reduced.
Virtual Components	Not introduced	Not introduced	Introduced in Prediction module
IS test	Not introduced explicitely	Solving the Basic Contradiction condition	Six tests to prove whether the End Solution is an Ideal Solution

2. Concise Description of BTIPS Application

BTIPS algorithm consists of five operations:

1. Identify and define precisely the problem, isolate it properly; the isolation should be right - isolating not too much nor too little; adequate space should be left for developing the solution.

2. Begin the BTIPS problem solving procedure by applying module Effects. Look for the physical, chemical, mathematical or technological effect that would solve the problem. If the End Solution (ES) is found, test whether or not it is the Ideal Solution (IS), if it is not, continue the search and apply module Principles.

3. To apply module Principles the Preliminary Solution (PrS) has to be found first. It should solve the main problem, even if creating another, hopefully simpler one. Having the PrS one should define how that solution improved the design situation (Improving Feature) and how it made the design situation more difficult (Worsening Feature), and formulate the Basic Contradiction (BC). Having defined the IF and WF, the principle(s) that would solve the BC and lead toward the End Solution (ES), should be chosen from the matrix of principles. If the ES is found and passes the obligatory tests, it would become the Ideal Solution (IS) and that is the end of the problem solving process. If it is not the IS, apply the next module - Prediction.

4. In preparation for application of the module Prediction one has to describe the Design System (DS), its components and their hierarchy. One should: a) describe the DS, b) locate the position of the system in the Super-System and locate the Sub-Systems, the Elements and Items, c) indicate the hierarchy of those components, d) examine the relations between components, e) eliminate the harmful actions or change them into neutral, f) change the neutral actions into positive, g) eliminate the harmful components, h) if after the above changes the Design System (DS) becomes the End Solution (ES), check whether or not it is the Ideal Solution (IS).

5. If the End Solution (ES) is still not fulfilling the expectations: a) add additional physical components, b) propose what components can be combined, c) propose what components can be still eliminated or reduced, d) decide where to delegate the functions of eliminated components; if the ES produced after those changes would turn to be the Ideal Solution (IS), this is the end of the process. If not, the Problem Statement (PS) should be changed and the search for the new ES applying BTIPS Principles should start from the beginning. Otherwise, virtual components should be introduced in the Designed System (DS) and DS should be analyzed again. If the DS with virtual components fulfils the expectations it becomes a Virtual System (VS). It would change again into DS after the development of technology that would allow to change Virtual Components (VC) into Physical Components (PC).

Note 1: If after any of the above operations 1 to 5, the End Solution (ES) fulfils all the expectations, it should be tested whether or not it is the Ideal Solution (IS), and if it is, this is the end of the process.

Note 2: To test the End Solution (ES) one should check six conditions, every one, except for d, necessary but not sufficient to prove that the ES is in fact the IS. The tests are following:

a) Is the basic contradiction solved by the ES? If yes, it may be the IS;

b) Is it possible to trim the ES? If the ES does not contain any unnecessary components to be trimmed, it may be the IS;

c) Is the information used to describe ES minimum? If yes, it may be the IS;

d) Can functions of the ES be separated? If yes, it may be the IS, but if not, it may still be the IS however not as attractive as expected;

e) Can the ES exist and operate using the minimum energy? If yes, it may be the IS;

f) Is the maintenance of the ES minimum? If yes, it may be the IS;

g) Are all the tests except for d satisfied? If yes, it is the IS and it is the end the process.

If the results of all the tests, except for d, are positive, the End Solution (ES) become a theoretical Ideal Solution (IS) and the process of solution search is successfully ended. In order however to change the IS into Practical Ideal Solution (PIS), conditions of feasibility, application, economy or sometimes even political and social conditions have to be also satisfied.

3. Application Examples

The examples of BTIPS problem solving applications are helpful in understanding the process. The following examples are chosen from literature, consulting and academic experience.

Example 1. Sand removal from a jet engine.

Synopsis. Problem statement: Remove sand from the air passing through a jet engine in a desert. Solution Method: BTIPS, module Effects. Physical effect used: centrifugal force. Function attained: Substance removal [9, 10, 11, 12 and 16].

Fig. 1. Views of a jet engine with additional side container (front and side) designed to take advantage of the

centrifugal force effect to remove the sand from the air flow [16]

Solution Process Description: The use of centrifugal force to remove sand particles is chosen (Figure 1). Problem statement in this example requires elimination of sand from a jet engine. From Physics one knows that if the mass is moving along the curve, it is subjected to the action of centrifugal force. If due to the rotation of blades a vertex in the air intake is created, the centrifugal force pushes the sand particles toward the walls of the engine shell (Figure 1) and outside. This effect is used to solve technological problem of particles separation from the air moving with high speed. [9, 10, 11, 12, 16].

Example 2. Preventing fire during quenching of steel parts in oil [9, 10 and 16].

Synopsis. Problem statement: Prevent fire during steel quenching in oil. Solution Method: BTIPS, module Principles. Preliminary solution: cut oxygen supply by covering the container with a lid. Improving Feature (IF): the lid prevents the oxygen supply, Worsening Feature: the lid hinders the crane operation. Basic Contradiction: there should be a lid and there should be no lid. Principles of Phase Transition was used to find the Ideal Solution - a lid made out of gas. This example, introduced by IM^TM [9], is a perfect one to illustrate the power of Principles. It demonstrates that use of matter in phases other than solid, may be a solution to numerous problems of technology [9], [10], [16].

Solution Process Description: The steel parts quenching in water has been used in blacksmith practice for centuries. In industrial quenching water is replaced by oil, improving the process but creating an oil fire problem. Basic contradiction is: the lid should be there to cut the oxygen supply and the lid should not be there because it hinders the crane operation. The principle of phase transition is used to solve the contradiction by proposing the lid made out of gas (Figure 2). Gas, that is heavier than air, stays on the surface of the oil and prevents the access of oxygen and leaves a free crane access to the container.

Fig. 2. A conceptual design of a gas lid covering the container and the quenched part before (left) and after (right) submersing in the oil [9], [10], [16]

The End Solution applied - is the lid made of gas (Figure 2) [16] is also the theoretical Ideal Solution (IS). It is not a Practical Ideal Solution (PIS) however because the use of the suggested least expensive gas CO₂ would be the most economical but not socially correct. For the climate change prevention reason the other, heavier than air gas, and should be used.

Example 3. Improving the breaking action of car tires on a pavement [9, 10, and 16].

Fig. 3. Schematics of the electric heating wire connections for heat generation in the pavement suggested by a TechOptimizer [10]; a system of such hearing wires embedded in the pavement would keep the pavement warm and dry and breaking action will be effective and save [16]

Example 3. Improving the breaking action on the highway pavement [9].

Synopsis. Problem statement: Prevent tire slipping on the pavement. Solution Method: BTIPS, module Prediction. System 1: A car tire. System 2: A road pavement. Subsystem added to system 2: A set of heating wires. Theoretical Ideal Solution: Heated pavement.

Solution Process Description: In winter time car’s tires (system No.1) will get cold, which makes rubbers stiff and hardened. The hardened tires are slippery and do not secure enough friction for braking [10, 15]. The End Solution is the introduction of the sub-system – electric heating wires into the system No.2, the pavement [16]. This is the ES that could became the theoretical IS. If the solar batteries by the highway could supply the electricity, this solution would pass an energy optimization requirement. Inserting heating wires into the pavement is an Ideal Solution (IS).

Solution Process Description: The problem of car braking on the highway, especially in a hilly terrain and during bad winter whether, is important for safety and travel comfort. Heating wire system is the Ideal Solution (Figure 3) [15.] The wires supply heat into the pavement, improve braking action, and have no negative effects on the tires nor on pavement [15].

4. Significance of Problem Solving and Engineering Design

The Alshuller’s problem solving method is still useful and attractive. It requires however further development to meet the newest demands of technology. BTIPS has been created to do it [12], [14], [15] and [16]. The key to “solve impossible” problem is in the user’s knowledge of science and technology, problem solving tools and the information about environment, in which the problem to be solved exists. The world is composed out of matter that could be present in four phases. Traditionally the solid phase is used the most. Engineers should be prepared however to understand all the phases of matter and be prepared to apply them in design and in production of goods. Possibility of solving problems with conflicting constrains depends often on application of different phase of matter or fields surrounding them. It determines the success of the product designed and give the companies and organizations that launched the product significant advantage over their competitors. The importance of problem solving knowledge should be brought to the engineering education as early as possible, starting not only during the beginning years of the university studies but even in high schools, It should be always in the focus of the attention of practicing engineers, scholars and industrialists and should also be brought to the attention of the general public.

Conclusions

Problem Solving in Engineering conceptual design is the key for successful development of industrial production, economy and the wellbeing of society. Facing the challenge of the 21^st century, general engineering problem solving research, education and practice has to be developed further. Engineering design is a foundation for the automated manufacturing and production. It is important to continue research on engineering problem solving in conceptual design and manufacturing. It could be done by further development of algorithmic problem solving methods that can be utilize in engineering education, research and practice. The correct use of these methods should be stressed. This is the reason that powerful but simple problem solving methods should be still developed. They should be supported by development of the appropriate software. They should be applied in industrial practice and research as well as in teaching and learning. Altshuller’s method of problem solving is still an important tool that should be conserved and developed further. It is important not only for achieving practical industrial goals but also for engineering education starting in high schools and during the first years of the universities studies. BTIPS is the method that can be utilized in this process.

Acknowledgement

The author is grateful to organizers of CAD/CAM/PDM-2016 in Moscow, Russia for allowing him to present in absentia this paper on problem solving in engineering conceptual design and perhaps to initialize an internet discussion. The author appreciates the encouragement of Dr. Valery Tsourikov during the start and continuation of this research. Many thanks go to IM^IM Corporation for the IM^IM and TechOptimizer Software grants. Expression of gratitude go also to IHS Inc. for the GoldFire software. Thank you for suggestions that came during the UConn/IM professional engineers courses and for those that came from the University of Connecticut student class reports and projects. Thanks for the materials received from institutions and private individuals that allowed to improve the courses, were used during them and influenced this article. The author appreciates very much suggestions from students and is grateful for students’ helpful attitude and cooperation. Many thanks go to Steve White of Mechanical Engineering. University of Connecticut for computer software application help.

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