Timely provision of quality products at the lowest prices possible has become the utmost competitive edge being pursued by virtually all manufacturing firms. They endeavour to speed up their production and deliveries of goods to end customers in order to make more money and even survive in the fierce competition arena.
Although much progress has been made in operations management and a series of production planning approaches have been proposed to achieve various manufacturing operations goals, optimisation results are often rendered unrealistic and even misleading, for few studies have considered the overall corporate goal of shareholder wealth maximisation and the specific economic environments where manufacturing firms operate. Some critical factors closely related to interests of corporate owners, such as working capital management and capital structure, are rarely involved in an overwhelming majority of production planning problems. Moreover, the overlook of the effects of production planning results on the environment makes them more impractical and even unavailable in real-world manufacturing environments.
To this end, the dissertation proposes a stochastic production planning model for the uncertain make-to-order production environment, with the focus mainly on the lot sizing decision-making policy. The primary goal of the optimization problem is to maximise the sustainable full interests of corporate owners, namely, the shareholder wealth, rather than to optimise some traditional local or short-term objective functions, such as work flow times, accounting costs, accounting profits and the like. To improve the generality and exactness of the proposed model, all involved uncertain random events are characterized by their own inherent statistical merits without any impractical assumptions on their distributions.
The improvement of production planning is not the only one single source of the wealth-based business performance. There are also some other critical factors which can impose direct influences on shareholder wealth. Among these potential shareholder wealth drivers, we choose to examine the effective management of working capital and capital structure, for they are closely pertinent to a firm’s financial position and its cash flow status.
In addition, environmental protection has in recent decades aroused extensively global attention because of its far-reaching impingements on the social and economic developments of the world. The carbon emission in production, especially its main component—carbon dioxide, is generally recognized as the most important emission source. To mitigate their diverse interference with the climate and the environment, a wide range of emission reduction measures, laws, and legislations has been enacted and implemented, making production planning optimisations more complicated. To better reflect the emerging production planning environment facing manufacturing firms, the emission trading system for carbon management, which has thus far become the most popular market-based carbon reduction mechanism, is incorporated into the proposed production planning model.
To theoretically and analytically validate the proposed approach, the probability and convex theories are adopted to prove the convexity or concavity of the optimisation objectives and the relevant global optimal characteristics. Numerical experiments are further conducted to demonstrate the important implications of the proposed optimisation model to production planning in industrial practices. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/206462 |
| Date | January 2014 |
| Creators | Wang, Xiaojun, 王晓军 |
| Contributors | Choi, SH |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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