Gyeongbeom Yi

Conversion of coal fly ash into zeolite and heavy metal removal characteristics of the products

Fly ash obtained from a power generation plant was used for synthesizing zeolite. Zeolites could be readily synthesized from the glassy combustion residues and showed potential for the removal of heavy metal ions. By the use of different temperatures and NaOH concentration, five different zeolites were obtained: Na-P1, faujasite, hydroxy sodalite, analcime, and cancrinite. The synthesized zeolites had greater adsorption capabilities for heavy metals than the original fly ash and natural zeolites. Na-P1 exhibited the highest adsorption capacity with a maximum value of about 1.29 mmole Pb g-1 and had a strong affinity for Pb2+ ion. The metal ion selectivity of Na-P1 was determined as: Pb2+> Cu2+> Cd2+> Zn2+, consistent with the decreasing order of the radius of hydrated metal ion. The adsorption isotherm for lead by Na-P1 fitted the Freundlich rather than the Langmuir isotherm.

Intermediate storage tank operation strategies in the production scheduling of multi-product batch processes

Abstract Multi-product batch processes use intermediate storage tanks to increase plant productivity and operational efficiency. In this paper, relations are developed for production scheduling models of the multi-product batch processes with storage time constraints of the intermediate storage tank. Numerical formulas are obtained to determine the makespan and the completion times of products on each unit. These results are extended to accommodate the general serial process networks with storage time and the product constraints of the intermediate storage tank. Next, the effects of the location and the number of the intermediate storage tank on the production scheduling are considered. From the above analysis, a MIPL model to find the maximum makespan is proposed. Applications of the developed model are presented with an example.

OPTIMAL DESIGN OF MULTIPLE BATCH UNITS WITH FEEDSTOCK/PRODUCT STORAGES

This article derives an analytical solution for determining the optimal size of the multiple batch unit plant with storage units. The total cost to be minimized consists of the setup cost of the batch processing units, the inventory holding cost of feedstock/product storage and the capital cost of the batch and storage units. A novel approach, which is called the PSW(Periodic Square Wave) model, is applied to represent the material flows among the batch and storage units. The PSW model presumes that the material flow between unit and storage is a periodic square shaped wave. The resulting optimal batch size has similar characteristics to the classical economic lot sizing model such as EOQ or EPQ model in the sense that the batch size is determined as the balance between setup and inventory holding cost. However, the influence of inventory holding cost of the PSW model is different from that of EOQ/EPQ model. The EOQ/ EPQ model includes only the product inventory holding cost while the PSW model includes all inventory holding costs around the batch unit. The PSW model is suitable for analyzing interlinked batch-storage system and is more accurate rather than EOQ/EPQ model. The optimal lot size of the PSW model is much smaller than that of EOQ/EPQ model as shown at an example. This is quite a remarkable result considering that the EOQ/EPQ model has been widely used over the last half century.

Optimal operation of quality controlled product storage

Abstract The mixed integer linear programming model has been developed for the production scheduling of polybutene (PB) process of Daelim Industrial Co. (DIC) in Korea. The PB process is composed of one reactor, 13 storage tanks and two package types. It produces seven reactor products. Most of the tanks are practically dedicated to a specific product but in general, any tanks can be shared by multiple products. Also, two major products use multiple tanks. The reactor is operated on block mode. The products are liquid and they should be stored in tanks before packaging. The unique characteristics of this scheduling problem exists on the fact that the product in tank should be locked for 3–15 days in order to check the quality specifications after run-down from the reactor. The primary objective of scheduling is reducing the number of quality checking process because it causes great loss in production time and tank utilization. The model is composed of about 1500–2000 integer variables. The branching priorities are adjusted according to the importance of variables based on current manual scheduling practice and it greatly enhanced the convergence of mixed integer model. The scheduling system was successfully implemented in real plant and replaced the manual work of scheduler.

Optimal Design of Process-Inventory Network Considering Late Delivery Costs

This study deals with stockout costs in the supply chain optimization model under the framework of batch-storage network. Stockout is very popular in chemical industries. Estimating stockout cost involves an understanding of customer reactions to a seller being out of stock at the time the customer wants to buy an item. This involves massively non-trivial work such as direct customer interviews and extensive mail survey. In this study, we will introduce a new interpretation of stockout costs combined with batchstorage network optimization model and thus suggest an easy way of estimating stockout costs. Optimization model suggest that optimal process and storage sizes considering stockout cost are smaller than those that do not consider stockout cost. An illustrative example support the analytical results.

Optimal Design of Process-Inventory Network under Cycle Time and Batch Quantity Uncertainties

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

OPTIMAL DESIGN OF MULTISITE BATCH-STORAGE NETWORK UNDER SCENARIO-BASED DEMAND UNCERTAINTY

An effective methodology is reported for the optimal design of multisite batch production/transportation and storage networks under uncertain demand forecasting. We assume that any given storage unit can store one material type that can be purchased from suppliers, internally produced, internally consumed, transported to or from other plant sites, and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between plant sites. The objective for optimization is to minimize the probability averaged total cost, which consists of the raw material procurement cost, the cost of setting up processes, inventory holding costs of the storage units, and the capital costs of processes and storage units. A novel production and inventory analysis formulation, the PSW (periodic square wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sizes, and the second is a separable concave minimization network flow sub-problem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of large-scale supply chain systems.

Optimal Design Of Batch-Storage Network with Financial Transactions and Cash Flows

This paper presents an integrated analysis of production and financing decisions. We assume that a cash storage unit is installed to manage the cash flows related with production activities such as raw material procurement, process operating setup, Inventory holding cost and finished product sales. Temporarily financial investments are allowed for more profit. The production plant is modeled by the Batch-Storage Network with Recycle Streams in Yi and Reklaitis (2003). The objective function of the optimization is minimizing the opportunity costs of annualized capital investment and cash/material inventory while maximizing stockholder`s benefit. No depletion of all the material and cash storage units is major constraints of the optimization. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the cash and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems and analytical lot sizing equations under a mild assumption about the cash flow pattern of stockholder`s dividend. The first subproblem is a separable concave minimization network flow problem whose solution yields the average material flow rates through the networks. The second subproblem determines the decisions about financial Investment. Finally, production and financial transaction lot sizes and startup times can be determined by analytical expressions as far as the average flow rates are calculated. The optimal production lot and storage sizes considering financial factors are smaller than those without such consideration. An illustrative example is presented to demonstrate the results obtainable using this approach.

Adaptive model predictive inventory controller for multiproduct warehouse system

An inventory control system has been developed for a distribution system consisting of a single multiproduct warehouse serving a set of customers and purchasing products from multiple vendors. Purchase orders requesting multiple products are delivered to the warehouse in a process referred to as joint replenishment. The receipt of customer orders by the warehouse proceeds in order intervals and in order quantities that are subject to random fluctuations. The objective of warehouse operation is to minimize the total cost while maintaining inventory levels within the warehouse capacity by adjusting the purchase order intervals and quantities. An adaptive model predictive control algorithm is developed using a periodic square wave model to represent the material flows. The adaptive concept incorporates a stabilized minimum variance control-type input calculation coupled with input/output stream parameter predictions. The boundedness of the control output under the suggested algorithm is mathematically proven under the assumption that disturbances in the orders are bounded. The effectiveness of the scheme was demonstrated using simulations.

Optimal Design of Multiperiod Process-Inventory Network Considering Transportation Processes

The optimal design of batch-storage network by using periodic square wave model provides analytical lot sizing equations for a complex supply chain network characterized as multi-supplier, multi-product, multi-stage, non-serial, multi-customer, cyclic system including recycling and/or remanufacturing. The network structure includes multiple currency flows as well as material flows. The processes are represented by multiple feedstock/product materials with fixed composition which are very suitable for production processes. In this study, transportation processes that carry multiple materials with unknown composition are added and the time frame is changed from single period into multiple periods in order to represent nonperiodic parameter variations. The objective function of the optimization involves minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders in the numeraire currency. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a multiperiod subproblem for average flow rates and analytical lot-sizing equations. The multiperiod lot sizing equations are different from single period ones. The effects of corporate income taxes, interest rates and exchange rates are incorporated.