Ключевое слово: «triz»

In Madagascar, daily life is often interrupted by frequent power cuts and load shedding, a common occurrence that poses challenges to both households and enterprises, by impacting productivity. The cost of electricity in Madagascar is also notably high, further worsening the difficulties faced by many in accessing reliable power. The main purpose of the present research is to identify an ideal strategy to improve the performance of the State-Owned Electricity Producer and Provider JIro RAno Malagasy or JIRAMA. The methodology of this research consists of four key steps aimed at improving the performance of JIRAMA. The first step involves applying the Problem Stream Mapping or PSM to JIRAMA, based on the Value Stream Mapping or VSM concept of Lean management. This step aims to visualize and analyze the current state of operations within JIRAMA to identify areas for improvement. The second step focuses on conducting a Root Cause Analysis of a specific problem identified during the PSM phase. This analysis aims to uncover the underlying causes of the problem. The third step involves contradiction analysis, a method used to identify and resolve conflicting objectives within the organization, such as balancing technical losses and quick installation in electricity distribution systems. Finally, the fourth step applies the Teoriya Resheniya Izobretatelskikh Zadatch or TRIZ, Theory of Inventive Problem Solving in English. That process generates ideal strategies to the identified problem, leveraging principles and patterns of inventive thinking to overcome technical contradictions and improve overall performance. The findings of this research culminate in the development of generic solutions tailored to enhance the performance of the state-owned company. These generic solutions serve as the foundation for designing ideal strategies aimed at addressing the specific challenges faced by JIRAMA. A strategy roadmap is then created, outlining the steps and timelines for implementing these strategies to achieve the desired performance improvements within JIRAMA. The main conclusion is that recovering the company and improving its performance is possible.

Value analysis/value engineering (VA/VE) is a well-known method of technical and economic study of systems since the middle of the 20th century aimed at setting objectives to reduce the cost and functional performance of a system. Despite the widespread and successful utilisation of VA/VE, it has a number of guideline shortcomings related not only to the complexity of estimating the value of the system elements, but also to the uncertainty of unambiguous division of functions by these elements. In addition, the idea of VA/VE actually based on the principles of analysing the dissonance of system parameters can often be applied without relying on the functions of system elements. The Operation Principal Evolution with Cost-Value Analysis (OPECVA) methodology was developed to address these and other shortcomings of VA/VE: among other things, it utilises the Saaty's pairwise comparison method to compare the elements of a system in terms of certain parameters. The OPECVA methodology was implemented in the Compinno-TRIZ software package. The paper describes three types of OPECVA: OPECVA of objects and structures, OPECVA of functions and OPECVA of processes. The OPECVA of flows is reduced to the OPECVA of objects or the OPECVA of processes.

The article discusses two fundamental strategies for integrating the Theory of Inventive Problem Solving (TRIZ) and Artificial Intelligence (AI): “TRIZ+AI” and “AI+TRIZ”. Using the Compinno-TRIZ and AutoTRIZ software packages as examples, their capabilities and limitations are demonstrated. The authors propose a methodology for assessing the level of inventive thinking in AI based on the component model of TRIZ. It is shown that modern AI models, such as GPT, demonstrate a level of inventive thinking comparable to that of a second-year university student. The most promising areas of their application are the stages of problem analysis and refinement of solutions, whereas the generation of fundamentally new solutions remains the domain of the human expert.