Review on bio-based plastic for future applications

This paper reviews the future applications of bio-based plastics. Most plastics are made through petrochemical processes. In other words, they start out as the chemical byproducts of oil refining, which are turned into a variety of plastics through chemical processes that form long molecular chains known as polymers. These polymers give plastics their structure. Bioplastics are biodegradable materials that come from renewable sources and can be used to reduce the problem of plastic waste that is suffocating the planet and contaminating the environment. The advantages of using bioplastics are bioplastics won’t leach chemicals into food, non- toxic and offer a zero waste end life options. Bioplastics can be recycled with conventional plastics to produce a great material for food packaging. It also has a socio�economic benefit that often have a positive impact on the consumers who are increasingly becoming aware of environmental issues. As conclusion, it is proven that bioplastics give promising future to cleaner and safer world

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

EXPERIENCE-ORIENTED MODEL OF BUDGET ALLOCATION AND COST CONTROL FOR ENGINEERING CONSULTING PROJECTS

This paper presents an experience-oriented model of budget allocation and cost control for engineering consulting projects. The proposed model comprised two modules: a work item module and a work duration module. Regarding the work item module, a project manager employed the analytic hierarchy process (AHP) to determine the budget percentage allocated to each work item. Regarding the work duration module, this study compiled all S-curves appearing in each budget percentage range in past projects. A project manager then selected the optimal curve shape for each work item to determine the daily budget allocation and cost control limits throughout the work duration of each work item. Testing revealed that the proposed model facilitates project managers’ budget allocation decision-making, determines budget control limits for the overall project and for each work item and identifies work items that may be out of control at an early stage

Optimization-Based Architecture for Managing Complex Integrated Product Development Projects

By the mid-1990\u27s, the importance of early introduction of new products to both market share and profitability became fully understood. Thus, reducing product time-to-market became an essential requirement for continuous competition. Integrated Product Development (IPD) is a holistic approach that helps to overcome problems that arise in a complex product development project. IPD emphasis is to provide a framework for an effective planning and managing of engineering projects. Coupled with the fact that about 70% of the life cycle cost of a product is committed at early design phases, the motivation for developing and implementing more effective methodologies for managing the design process of IPD projects became very strong. The main objective of this dissertation is to develop an optimization-based architecture that helps guiding the project manager efforts for managing the design process of complex integrated product development projects. The proposed architecture consists of three major phases: system decomposition, process re-engineering, and project scheduling and time-cost trade-off analysis. The presented research contributes to five areas of research: (1) Improving system performance through efficient re-engineering of its structure. The Dependency Structure Matrix (DSM) provides an effective tool for system structure understanding. An optimization algorithm called Simulated Annealing (SA) was implemented to find an optimal activity sequence of the DSM representing a design project. (2) A simulation-based optimization framework that integrates simulated annealing with a commercial risk analysis software called Crystal Ball was developed to optimally re-sequence the DSM activities given stochastic activity data. (3) Since SA was originally developed to handle deterministic objective functions, a modified SA algorithm able to handle stochastic objective functions was presented. (4) A methodology for the conversion of the optimally sequenced DSM into an equivalent DSM, and then into a project schedule was proposed. (5) Finally, a new hybrid time-cost trade-off model based on the trade-off of resources for project networks was presented. These areas of research were further implemented through a developed excel add-in called “optDSM”. The tool was developed by the author using Visual Basic for Application (VBA) programming language