A Monte-Carlo approach to tool selection for sheet metal punching and nibbling

Selecting the best set of tools to produce certain geometrical shapes/features in sheet metal punching is one of the problems that has a great effect on product development time, cost and achieved quality. The trend nowadays is, where at all possible, to limit design to the use of standard tools. Such an option makes the problem of selecting the appropriate set of tools even more complex, especially when considering that sheet metal features can have a wide range of complex shapes. Another dimension of complexity is limited tool rack capacity. Thus, an inappropriate tool selection strategy will lead to punching inefficiency and may require frequent stopping of the machine and replacing the required tools, which is a rather expensive and time consuming exercise. This work demonstrates that the problem of selecting the best set of tools is actually a process of searching an explosive decision tree. The difficulty in searching such types of decision trees is that intermediate decisions do not necessarily reflect the total cost implication of carrying out such a decision. A new approach to solve such a complex optimisation problem using the Monte Carlo Simulation Methods has been introduced in this thesis. The aim of the present work was to establish the use of Monte Carlo methods as an "assumptions or rule free" baseline or benchmark for the assessment of search strategies. A number of case studies are given, where the feasibility of Monte Carlo Simulation Methods as an efficient and viable method to optimise such a complex optimisation problem is demonstrated. The use of a Monte Carlo approach for selecting the best set of punching tools, showed an interesting point, that is, the effect of dominant "one-to-one" feature/tool matches on the efficiency of the search. This naturally led on to the need of a search methodology that will be more efficient than the application of the Monte Carlo method alone. This thesis presents some interesting speculations for a hybrid approach to tool selection to achieve a better solution than the use of the Monte Carlo method alone to achieve the optimum solution in a shorter time

On the Product Development Times in various Market Properties

In this paper we present a decision analytic to analyze different product development scenarios and obtain the optimal recommendation on the product development time. These scenarios differ in many aspects such as the product complexity level, the competitor's quality level, price demand-sensitivity. The objective to generate managerial insights on how much time should a company spent in the development when theses market characteristics differ. In general, product development time is sensitive to this market and yet the optimal strategy varies.© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

The application of agent-based modelling for the diffusion of innovation research: a case study

Agent-based modelling (ABM) is considered as an important technique to study innovation diffusion and has been increasingly applied in the diffusion of innovation activities. This study investigates the opportunities to adopt ABM to diffuse innovation in a construction company in Oman, engaged in an innovative project to construct a prestigious integrated township. It proposes a new innovation diffusion model that simulates the social interactions between agents and how that interaction influences the agent's (visitors) adoption decisions. The application of ABM in this case project is analysed through MATLAB simulation software. The result from the study shows how a more complex model of a society can be implemented in a commonly used platform. The simulation results showed how the proposed model can actually mimic the expected behaviour of a complex system where static characteristics of agents such as nationality and age may influence the dynamic characteristics such as talking and frequency of visiting a certain location, which enhances the rate of decisions making process.©2023 Inderscience.fi=vertaisarvioitu|en=peerReviewed