Inventory analysis of the timber industry in Ghana

Background, aim, and scope The timber sector, i.e., forestry and timber industry, plays an important role in the socioeconomic development of Ghana through timber products export. Timber production in this sector is associated with increasing environmental burdens in terms of use of materials and energy, production of emissions and waste, and land use changes. The purpose of this study was to compile a comprehensive life cycle inventory (LCI) to identify the most dominant environmental pressures for five major production lines in the timber industry, and to evaluate the influence of the choice of the functional unit on the results (1 m3, 1 kg, and 1 euro). LCA’s of wood typically base their functional unit on volume, but mass or money may be more appropriate for the rather different products considered in this study. Materials and methods The LCI covers five timber production lines, namely, air-dried lumber, kiln-dried lumber, plywood, veneer, and furniture parts. Three functional units were used for this study to identify the most appropriate basis for a fair comparison of the different timber products (functional units were 1 m3, 1 kg and 1 euro). Questionnaires were administered to thirty selected companies in Ghana. These companies provided data about their material uses, energy requirements, and waste production for their operations from 2000 to 2007. The collected data were first converted into total annual average values, and next extrapolated to reflect the national average data for all 104 active companies. Finally, these data were expressed per functional unit for each of the five product lines on the basis of their production outputs (in volume, mass or money according to functional unit applied). Forest land used changes data was taken from the Ghana Timber Industry Development Division. Emissions for the several activities were taken from literature. Results and discussion Land use change for timber production in Ghana between the estimated periods turned out to be 34.0¿×¿103 ha per year, which will lead to complete deforestation in the year 2023 if continued. The total energy consumed by the timber sector per year was estimated at 1.9¿×¿109 MJ per year. The results showed that CO2 emissions by the timber sector activities per year accounted for 745k tons per year and dominate overall greenhouse gases emissions in the timber sector (changes in carbons storage related to land use changes not included). Wood waste by the timber sector accounted for 0.8 million m3 per year. The enormous wastage of wood contributes enormously to the rapid depletion of the country’s timber resources. The choice of the functional unit influences inventory results. The money-based functional unit, which also seems more appropriate for the different products considered, favors the value-added. Value-added products with strict sustainable forest management policy hold a promising future in terms of sustainability for the timber industry in Ghana. Conclusions This study has yielded good quality primary data unique for LCA research in Africa. This will enhance LCA approaches in Ghana, and allows here identification of the main environmental pressures and their dominantly contributing processes in the timber sector. Land use changes due to forestry form a critical issue and require urgent attention. The chosen functional units’ plays a crucial role in the environmental comparison of production line in the timber sector in Ghana. Recommendations and perspectives A comprehensive and transparent inventory for the timber industry provides the industry with an overview of areas in which material and thus economic savings can be made for the good of both environment and the industry finances. Good data keeping in the Ghanaian timber industry will help to build the required research capacity to develop local familiarity and competence in LCA techniques and applying these techniques will help to further certify tropical timber international markets

[[alternative]]The Study of Supply Chain Inventory Model with Price-Sensitive Demand and Trade Credit

計畫編號：NSC96-2416-H032-007研究期間：200708~200807研究經費：460,000[[abstract]]在現今競爭性的市場環境，企業已經由獨立決策改變為協同合作來制定策略。為降 低成本及改善服務水準，有效的供應鏈策略必須考慮在供應鏈中不同層級之間的互動關 係。在複雜的供應鏈中，存貨的控制是相當困難的工作，而且對顧客的服務水準及整體 供應鏈系統的成本有顯著的影響。因此，在供應鏈管理（Supply Chain Management, SCM）模式下建立適當的整合存貨模型，如何決定同一供應鏈上合作夥伴的最適庫存/ 訂購策略，使得存貨相關總成本為最小或總利潤為最大，是本研究的主要內容。 本研究為二年期的研究計畫，將在考量商品的需求量隨價格變動(即需求率為銷售 價格的遞減函數)，且允許信用交易(供應商允許零售商延遲付款)下，分別建立適當的 整合存貨模型，以決定供應鏈中供應商與零售商的最適存貨策略。第一年在需求率固 定、且供應商允許零售商延遲付款的情況下，嘗試建立分別以供應商為領導者（零售商 為跟隨者）、零售商為領導者（供應商為跟隨者）及雙方合作的供應鏈存貨模型，並求 出Stackelberg 均衡解。。第二年在市場需求率為零售商銷售價格的遞減函數，且供應商 允許零售商延遲付款的情況下，考量非合作與合作賽局策略，建立並求解供應商與零售 商的最佳存貨決策模式。我們將嘗試利用數學證明最佳解存在的充分且必要條件，接著 建立一個演算法求出使得單位時間總利潤有最大值的最適解。最後，以數值範例說明求 解過程，並對重要的參數值進行敏感性分析。[[sponsorship]]行政院國家科學委員

Solving for an Optimal Batch Size for a Single Machine Using the Closed-form Equations to Minimize Inventory Cost

Batch sizing strategy in the manufacturing system has significant impacts on the production performance. In the previous research studies, researchers proposed complicated techniques such as optimization models, simulation, queuing theory, and complex algorithms to solve for the optimal batch size. Using those techniques are difficult for plant managers to calculate for the optimal batch size. Therefore, the closed-form optimal batch size equations are proposed to minimize inventory cost of 2 models. The first model is illustrated when the inventory cost is associated with holding cost but without setup cost. The second model is illustrated when inventory cost is associated with both holding cost and setup cost. Besides the optimal batch size calculation, the value of λ, which is the shadow price of the available setup time, is also solved for sensitivity analysis purpose. Application of the closed-form equation is provided with various parameters applied to different products. The results show that the proposed closed-form equations approach performs well and verifies the effectiveness of the approach

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry

Integrating logistics and production

The purpose of this research project is to help a supply chain manager to decision making easier in order to deliver final product on time to final customer. Coordination between all members of a supply chain are essential to achieve this objective and reduce bullwhip effect. The members considered on this thesis are going to be a manufacture, its supplier and supplier of that supplier (sub-supplier). A common purchase forecast is done thanks to Collaborative Planning Forecasting and Replenishment (CPFR) using an order point policy. A dashboard is elaborated with Key Performance Indicators (KPI) and graphics that shows the status of the supply chain. Then a simulation of a real case test how robust is the supply chain using normal random variables and evaluate how good and reliable are each of the members of the supply chain. At the end of the project there is a little experiment where a supply chain is checked with two different scenarios in which stability of demand are different. The results of that projects show an easy to use dashboard which evaluate a supply chain and its members and gives numerical and graphic information to the manager

Supply chain coordination and integration under yield loss

The primary objective of this dissertation is to develop analytical models for typical supply chain situations to help supply chain decision-makers under supply yield loss. We derive solution procedures for each model and present several managerial insights obtained from our models through numerical examples. Additionally, this research provides decision-makers insights on how to incorporate uncertainty in demand and supply and shortage information into a mathematical model. This study deals with three forms of integrated cost-profit models under different scenarios including coordination policy and supply yield loss in a two-stage supply chain involving a retailer and a supplier, dealing with a single product under deterministic condition. We compare the profits of the whole supply chain system under the coordinated policy with those of individual decision making approaches and demonstrate the efficiency of coordination. These models attempts to find the optimal solutions for the retailer’s order quantity, quality level, amount of emergency procurement, and the production and shipment decisions of the supplier, so that the resulting joint total profit for the entire supply chain is maximized. We illustrate our model and the potential benefits of outsourcing in a supply chain system through a numerical example. Extending the analyses obtained above, we then develop models for an integrated supplier–retailer supply chain under imperfect production and shortages, with the additional decision variable of market pricing on the part of the retailer. We assume that market demand is sensitive to the retailer’s selling price and study the combined operation and pricing decisions in the supply chain. We develop profit maximization models for the cases of independent and joint optimization. The results of obtained from our analyses demonstrate that the individual profit, as well as joint profit can be increased by our suggested model, under a non-linear price dependent demand function. In addition, the results with retailer-supplier coordination tend to be superior, which leads to illustrate that setting appropriately retailer’s selling price can increase market demand and the profits of both parties, as well as that of the supply chain. Finally, numerical examples are presented to illustrate these models, and the sensitivity analyses of a selected set of model parameters on the total profit is conducted. A major finding of this study is that coordination between the retailer and the supplier improves channel profit significantly. Furthermore, the possibility of external procurement tends to improve total system profitability as the price sensitivity of demand increases.Ph.D., Business Administration -- Drexel University, 201

Optimising Supply Chain Performance via Information Sharing and Coordinated Management

Supply chain management has attracted much attention in the last decade. There has been a noticeable shift from a traditional individual organisation-based management to an integrated management across the supply chain network since the end of the last century. The shift contributes to better decision making in the supply chain context, as it is necessary for a company to cooperate with other supply chain members by utilising relevant information such as inventory, demand and resource capacity. In other words, information sharing and coordinated management are essential mechanisms to improve supply chain performance. Supply chains may differ significantly in terms of industry sectors, geographic locations, and firm sizes. This study was based on case studies from small and medium sized manufacturing supply chains in People Republic of China. The study was motivated by the following facts. Firstly, small and medium enterprises have made a big contribution to China’s economic growth. Several studies revealed that most of the Chinese manufacturing enterprises became aware of the importance of supply chain management, but compared to western firms, the supply chain management level of Chinese firms had been lagging behind. Research on supply chain management and performance optimisation in Chinese small and medium sized enterprises (SMEs) was very scarce. Secondly, there had been plenty of studies in the literature that focused on two or three level supply chains whilst considering a number of uncertain factors (e.g. customer demand) or a single supply chain performance indicator (e.g. cost). However, the research on multiple stage supply chain systems with multiple uncertainties and multiple objectives based on real industrial cases had been spared and deserved more attention. One reason was due to the lack of reliable industrial data that required an enormous effort to collect the primary data and there was a serious concern about data confidentiality from the industry aspect. This study employed two SME manufacturing companies as case studies. The first one was in the Aluminium industry and another was in the Chemical industry. The aim was to better understand the characteristics of the supply chains in Chinese SMEs through performing in-depth case studies, and built models and tools to evaluate different strategies for improving their supply chain performance. The main contributions of this study included the following aspects. Firstly, this study generalised a supply chain model including a domestic supply chain part and an international supply chain part based on deep case studies with the emphasis on identifying key characteristics in the case supply chains, such as uncertainties, constraints and cost elements in association with flows and activities in the domestic supply chain and the international supply chain. Secondly, two important SCM issues, i.e. the integrated raw material procurement and finished goods production planning, and the international sales planning, were identified. Thirdly, mathematical models were formulated to represent the supply chain model taking into account multiple uncertainties. Fourthly, several operational strategies utilising the concepts of just-in-time, safety-stock/capacity, Kanban, and vendor managed inventory, were evaluated and compared with the case company's original strategy in various scenarios through simulation methods, which enabled quantification of the impact of information sharing on supply chain performance. Fifthly, a single objective genetic algorithm was developed to optimise the integrated raw material ordering and finished goods production decisions under (s, S) policy (a dynamic inventory control policy), which enabled the impact of coordinated management on supply chain performance to be quantified. Finally, a multiple objectives genetic algorithm considering both total supply chain cost and customer service level was developed to optimise the integrated raw material ordering and finished goods production with the international sales plan decisions under (s, S) policy in various scenarios. This also enabled the quantification of the impact of coordinated management on supply chain performances

Modelling of Coordinating Production and Inventory Cycles in A Manufacturing Supply Chain Involving Reverse Logistics

In today’s global and competitive markets selling products at competitive prices, coordination of supply chain configuration, and environmental and ecological consciousness and responsibility become important issues for all companies around the world. The price of products is affected by costs, one of which is inventory cost. Inventory does not give any added value to products but must be kept in order to fulfill the customer demand in time. Therefore, this cost must be kept at the minimum level. In order to reduce the amount of inventory across a supply chain, coordination of decisions among all players in the chain is necessary. Coordination is needed not only for a two-level supply chain involving a manufacturer and its customers, but also for a complex supply chain of multiple tiers involving many players. With increasing attention being placed to environmental and ecological consciousness and responsibility, companies are keen to have a reverse supply chain where used products are collected and usable components remanufactured and reused in production to minimize negative impacts on the environment, adding further complexity to decision making across a supply chain. To deal with the above issues, this thesis proposes and develops the mathematical models and solution methods for coordinating the production inventory system in a complex manufacturing supply chain involving reverse logistics and multiple products. The supply chain consists of tier-2 suppliers for raw materials, tier-1 suppliers for parts, a manufacturer who manufactures and assembles parts into finished products, distributors, retailers and a third party who collects the used products and returns usable parts to the system. The models consider a limited contract period among all players, capacity constraints in transportation units and stochastic demand. The solution methods for solving the models are proposed based on decentralized, semi-centralized and centralized decision making processes. Numerical examples are used by adopting data from the literature to demonstrate, test, analyse and discuss the models. The results show that centralised decision making process is the best way to coordinate all players in the supply chain which minimise total cost of the supply chain as a whole. The results also show that the selection of the length of limited horizon/ contract period will be one of the main factors which will determine the type of coordination (decentralised, centralised or semi-centralised) among all players in the supply chain. We also found that the models developed can be viewed as generalised models for multi-level supply chain by examining the models using systems of different tiers from the literature. We conclude that the models are insensitive to changes of input parameters since percentage changes of the supply chain’s total cost are less than percentage changes of input parameters for the scenarios studied