Towards A Model/Framework for Optimizing Automated Engineering
Systems in Developing Countries.
Muhammad Mansoor
School of Engineering, University of Plymouth, Plymouth. UK.
The field of Engineering Systems optimization has gained importance in the last few years. As a result engineering organizations are increasingly adopting better quality products and newer methods of production. In particular, developing countries are facing problems due to unavailability of advanced technologies and usage of conventional engineering structures/systems. In literature survey numerous models/frameworks exist for optimization of engineering systems. Several methodologies including TRIZ have been used in these models. These models address problems relating to overall process of optimization based on working pattern of engineers/workers. This has resulted in frameworks limited to work management optimization and/or optimized stepwise working of technical processes involved in optimization projects.
In this paper we identify the limitations of existing models and while using TRIZ methodology propose a preliminary guideline for preparing a generic model of optimizing automated engineering systems. We feel that this model will address the limitations imposed by previous models and aid in optimization of automated engineering systems. The suggested model is dependent on those automation specific critical engineering parameters/factors which are involved in working/development of automated engineering systems and their optimization. Paper proposes the guidelines in a flow chart form showing the existing problems, TRIZ path to be followed for solution and expected results. Applications of the proposed model/framework are also discussed.
This paper discusses opportunity of optimizing existing engineering systems in developing countries, which are having limited financial resources. Developing countries has long been trying in progress of engineering industry, but limited resources and finances have always been an issue towards adopting latest technology for producing the best quality in competition. The growing gulf in technological and scientific capacity between developed and developing countries has been a major source of concern for decades. This "technology divide" marginalises developing countries and makes it hard for them to meet their basic needs, participate in the global economy and manage the environment. The conventional response to this challenge has been to call for technology transfer from industrialised to developing countries. But decades of promises and diplomatic wrangling have produced precious few results [3]. Optimization of existing systems to reduce loses and produce better quality is a viable solution usually sought by industries having limited resources to cop with the demand in outer world. While working with optimizing the performance of some existing engineering system, it is a difficult task for engineering sector in developing countries, which is mostly relying on old/used equipments and not following the technology changes on regular basis. Optimization solutions whenever sought were always some project specific/prototype works starting
from scratch till end for each project, hence making an overall initial cost high enough that it is usually counted not feasible in terms of initial investment. Factors and parameters involved in technical growth or change in developing countries should be taken in account while proposing a theory or project in some developing country’s engineering sector scenario. These factors are usually old technology and financial resources limited, which is making it difficult to produce optimized solution with existent less developed technologies in engineering industry of developing countries.
Due to recent development in information technology (IT) and related fields, developing countries looking for industrial progress are encouraging use of latest IT enhanced technologies like automation for solving industrial problems with limited resources. Automation technologies are being used widely for optimizing overall industrial processes and producing good results for enhancing performance of existing engineering systems. The computer, in its hardened and non-hardened forms, has made it possible to control manufacturing more precisely and to assemble more quickly, factors which have increased competition and forced companies to move faster in today's market," wrote Leslie C. Jasany in Automation [5]. IT technologies are used for data collection, monitoring, control, real time feedback and troubleshooting for running engineering systems. Reducing losses results in increased efficiency and reducing risk creates better working of engineering system.
Definition of Optimization can be taken as an objective function which we want to minimize or maximize. A set of unknowns or variables which affect the value of the objective function. Variables might include time, weight, size, amounts of different resources etc. For this purpose automation technologies are providing good applications and services since last few years of exponential development in IT technologies and related fields. Now a day world it is, in short, using the computer to achieve the most efficient design of a product. In the past, design engineers performed a combination of manual and automated methods to accomplish design optimization. While Automation refers more to an ideal for industrial production than any one set of technologies or practices. The word was coined in 1946 by the Ford Motor Company's vice president, Dale S. Harder [5]. As a technology, automation can be applied to almost any human endeavor, from manufacturing to clerical and administrative tasks. The fundamental constituents of any automated process are (1) a power source, (2) a feedback control mechanism, and (3) a programmable command (see illustration) structure. The advances made in electronic computation and feedback have certainly contributed to the growth of automation [5].
Fig.1 Elements of an automated system [5]
Automation has played a major role in increasing productivity and reducing costs in service industries. In recent years, the manufacturing field has witnessed the development of major automation technologies. These technology alternatives include Information technology (IT) dependent resources as major components which encompasses a broad spectrum of computer technologies used to create, store, retrieve, and disseminate information. Technologies like Computer-aided manufacturing (CAM), Numerically controlled (NC) equipment, Robots, Flexible manufacturing systems (FMS), Computer integrated manufacturing (CIM) are different examples of available alternatives for automation of engineering industry systems. Being Considerate for use of automation-oriented alternatives is essential for manufacturing firms of all shapes and sizes.
While keeping in consideration the idea of this research for development of a framework or model, TRIZ methodology was thought to be adopted for finding the optimum solutions. Aim is to produce a framework for engineers/workers working for automation of engineering systems in developing countries which helps them with their task being systematic and innovative while following proper systematic engineering considerations.
In the optimization of a process chain the project team has to face a problem which is usually characterized by many requirements and objectives, some of which are conflicting. The team may have to solve a problem with no known solution. This is called an inventive problem and may contain contradictory requirements. Knowledge and creativity are two essential conditions for a successful solution. However, there is often a lack of both. Pfeifer, T., 2001 ./Lit 2/.[4]
Even though the composition of the team is interdisciplinary, it is virtually impossible to integrate universal knowledge of all specialized areas into a team. Independent studies have shown that creativity diminishes steadily throughout the work phase of life. Terninko, J., 1997 /Lit 3/ [4]. Many people hesitate to be creative, because they fear that they lack the essential skills. In general humans solve problems by analogical thinking. That is, we try to relate the problem we are facing to some standard class of problems (analogs) we are familiar with, and
for which a known solution exists. If we can draw the right analogy, we can find the right solution. Our knowledge of such analogous problems, however, is the result of our educational, professional, and life experiences. Ideally, all potential directions for solutions should be equally regarded. In reality however, only solutions within one's own experience are considered while the consideration of alternative technologies to develop new concepts is ignored. Altshuller, G.S., 1984 /Lit 4/ [4]. This results in what is called psychological inertia which defeats randomness and leads only into those areas of personal experience. For optimization of an engineering system it would be a decisive advantage if the team had an extensive knowledge base and was capable of generating innovative concepts purposefully and systematically, rather than more or less at random. The TRIZ method provides some suitable tools.
TRIZ is a methodology, tool set, knowledge base, and model-based technology for generating innovative ideas and solutions for problem solving. TRIZ provides tools and methods for use in problem formulation, system analysis, failure analysis, and patterns of system evolution (both 'as-is' and 'could be'). TRIZ, in contrast to techniques such as brainstorming (which is based on random idea generation), aims to create an algorithmic approach to the invention of new systems, and the refinement of old systems.
TRIZ research began with the hypothesis that there are universal principles of invention that are the basis for creative innovations that advance technology, and that if these principles could be identified and codified, they could be taught to people to make the process of invention more predictable. The research has proceeded in several stages over the last 50 years.
The three primary findings of this research are as follows [6]:
1. Problems and solutions were repeated across industries and sciences 2. Patterns of technical evolution were repeated across industries and
sciences
3. Innovations used scientific effects outside the field where they were developed General Solution Specific Solution Specific Problem General Problem
Genrich S. Altshuller felt a theory of invention should satisfy the following conditions:
1. be a systematic, step-by-step procedure
2. be a guide through a broad solution space to direct to the ideal solution 3. be repeatable and reliable and not dependent on psychological tools 4. be able to access the body of inventive knowledge
5. be able to add to the body of inventive knowledge
6. be familiar enough to inventors by following the general approach to problem solving [7]
TRIZ expands the knowledge horizon of the developer by using a scientific-engineering knowledge base and supports the user systematically throughout the process of creative problem solving. The method ensures an effective and efficient search for innovative solutions, focusing on the so-called Ideal Final Result. It limits the search field considerably, but fosters creativity within that search field. Herb, R.; Herb, T.; Kohnhauser, V, 2000. /Lit 5/ [4]. The proposed framework of this paper will be using different tools and methods of TRIZ while pursuing a solution for optimization.
Different research works conducted over optimization used different techniques to enhance the working of engineering systems. TRIZ and other technologies were used and models were proposed. Among those An Approach on Optimization [1], Holistic Value Framework [2], Innovative Process Chain Optimization [4] and others were referred for this paper and approaches used in those research works were studied, analyzed and compared. This paper proposes to develop a framework keeping in consideration of previous works and research, while aims to provide a generic solution which may help engineers/workers dealing with automation technologies for optimization of engineering systems. The approach taken suggests developing a model keeping in consideration all critical engineering parameters specifically involved in optimizing an automated engineering system while utilizing potentials of TRIZ approach. This may be referred as a framework towards lean manufacturing systems optimized by automation technologies, while considering critical engineering system parameters involved in such optimization. As generic model/framework it’ll be used for all low technology developing countries in general, as TRIZ research began with the hypothesis that problems and solutions were repeated across industries/sciences and there are universal principles of invention that are the basis for creative innovations.
Considering previous works which focused on different aspects of engineering systems and working for optimization of these engineering systems, we find that models/frameworks proposed and research analysis mainly addressed working patterns/Line of action for technical staff and solution seekers. This paper suggests that a framework should be produced, which specifically aim for automation focused works related to optimization and is dependent on those
automation specific critical engineering parameters/factors which are involved in development of automated engineering systems and their optimization.
The proposed working for development of this model can be summarized in following diagram showing the work needed and output expected from the proposed work.
The framework proposed will be considering all possible critical factors involved in automated optimization, which can be generalized in developing world’s engineering industry. It builds on hypothesis that the automated optimization projects can be linked to several independent/dependent critical factors and there is chance for a set of factors to share most of the optimization projects in developing countries’ existing engineering industry. While for getting an economically feasible projects scale, the average shared proportion of parameters/factors should be large enough. If the common factors change too frequently project to project, then it is difficult to form a generic model for
Project specific factors and parameters for individual projects to be conducted in different industries Generalized critical automated
optimization factors for less developed engineering systems
Solution worked out using Generic framework proposed and project specific
additional requirements(parameters) Existing engineering system deficiencies in developing countries Optimization considerations and aims in developing countries industry Automation technology and important engineering system parameters
Generic framework proposed for automated optimization of engineering systems in developing countries
automated optimization projects and again innovative works from scratch to final output of a project may need great investments. The paper proposes to build on some of previous ideas and thoughts further to develop a Holistic Framework that’ll incorporate diverse elements and techniques like ideality, function-based thinking, Nine Windows, Little People from TRIZ. The focus of this framework is to encourage the use of TRIZ methods of problem solving for optimization problems in industry of developing countries.
Defining the process, identifying value, functions, wastes and exploring the problem for solution landscape of some new optimization project can be performed better only of experts of different fields all work together in a single team for every new project which is practically not possible most of the times. This is where TRIZ gives the solution; TRIZ expands the knowledge horizon by providing a knowledge basis that represents the combined experience of over 2.5 million patents. It also helps users to detach themselves from their usual thought patterns and structures. Armed with TRIZ, the optimization team can generate innovative concepts for breakthrough solutions [4]. Producing a generic framework relating all common shared critical factors will contribute for automated optimization engineering projects. The palpable results of this framework/model development may result in a toolkit for producing quality output in automated optimization of resources limited engineering systems in developing countries. It may serve in parallel to factors varying project to project, producing easy cost effective solutions for all similar works.
Detailed literature reviews of previous related works will be considered, expert opinions will be obtained and case studies over automated optimization of engineering industries in developing countries will be conducted for producing practical results.
Summary
Considering shortcomings and limitations of resources in developing countries, there has been efforts enhancing the engineering industry performance with available resources. To compete in an open market with developed nations, which are having better resources and advanced technologies of engineering, developing countries have long been trying to produce quality which may compete with advanced engineering products of developed countries. With developments in IT related fields, automation technology has evolved as a cheaper solution of optimization for all such industries having limited financial resources.
To help automated optimization projects a framework should b developed which may be used as a base/tool for easy and appropriate solutions, while using minimum time and resources for projects study, analysis, evaluation and solution design. TRIZ is a methodology, tool set, knowledge base, and model-based
technology for generating innovative ideas and solutions for problem solving. TRIZ, in contrast to techniques based on experience and psychological methods, aims to create a systematic and logical stepwise approach to the invention of new systems, and the refinement of old systems. TRIZ may be used for finding a generalized solution based on those critical factors which are common between automated optimization projects in developing countries’ engineering industry scenario. This solution may be used as a base in parallel with project specific parameters which are different for different projects and may produce a quicker output for finding appropriate innovative solution in systematic ways.
Acknowledgements
I am thankful to Prof. Michael Riley, Dr. Pieter dewilde, Dr. Michael Miles, Ms veronica lattore for guiding me and supporting me all the way in my research until now. Their thoughts, knowledge sharing and guidance have shaped my thoughts and given me confidence to continue with my research works. I’m also thankful to Ms Saima Naurin from HEC, Pakistan and my funding agency HEC, Pakistan for their continuous kind support and help in all financial matters for my research work.
References
1. Huangao Zhang, Wenyan Zhao, Jianhui Zhang, Guoping Li, Runhua Tan: “An Approach on Optimization, Upgrade, Renewal of Product Platform”: 1-4244-0148/06; IEEE 2006
2. Karthikeyan Lakshminarayanan: “Holistic Value Framework – Creating Right Value Streams Using TRIZ and Other Concepts”.
3. Calestous Juma: “Developing Countries Work Around the 'Technology Divide'”: January 15, 2005 (Reprinted from New Scientist magazine)
4. Tilo Pfeifer, Martin Tillmann: “Innovative Process Chain Optimization - Utilizing the Tools of TRIZ and TOC for Manufacturing”. ETRIA World Conference- TRIZ Future 2003.
5. Automation: http://www.answers.com/topic/automation?cat=biz-fin
6. Katie Barry, Ellen Domb; Michael S. Slocum: “What is TRIZ?”: TRIZ Journal, http://www.triz-journal.com
7. Glenn Mazur: “Theory of Inventive Problem Solving (TRIZ)”:
8. Michelle M. Baron and M. Elisabeth Pat´e-Cornell: "Designing Risk-Management Strategies for Critical Engineering Systems": IEEE Transactions On Engineering Management, Vol.46, No.1, February 1999. 9. Ruth j. Boaden and Barrie Dale: "Justification of Computer-Integrated
Manufacturing: Some Insights into the Practice": IEEE Transactions On Engineering Management, Vol.37, No.4, November 1990.
10. Faramarz Maghsooflou, Ralph Masiello, and Terry Ray : “Energy Management Systems.” 1540-7977/04 IEEE.
11. Rob Bilderbeek & Erik Brouwer: "Innovation Indicators for the Technical Engineering Industry: A Meso Perspective": Dialogic, Utrecht, November 2000.
