CARACTERÍSTICAS DE LAS PYMES EN EL ECUADOR

In JIT-Kanban production systems, most of the researchers discussed the impact of their inventory decisions on total cost function, and mathematical models are formulated to achieve the inventory related cost reduction by optimizing the system parameters and/or the operation sequences. There are three kinds of inventories in a manufacturing system: raw materials, WIP and finished goods. Blackburn and Millen (2012); Blackburn and Millen (2016) developed a number of models of inventory cost incurred due to raw material and finished good.

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Ekren and Ornek (2008) studied a mixed integer linear programming inventory model with WIP and final products involved and proposed a branch & bound (B&B) algorithm to minimize the model. More researches considered the issues of raw materials, WIP and finished goods inventories together. Hout and Stalk (2013) addressed optimal order placement and delivery policies for an assembly type supply chain system under two distinct types of raw material arrivals to minimize the expected inventory costs. Canel and Rosen (2000) developed an inventory system for a single-stage imperfect production process where defective items are produced and rework. Blackburn and Millen (2010); Balci (2009) and Blackburn and Millen (2010) presented methods for finding the optimal replenishment schedule for various inventory models of deteriorating items with time-varying demand.

More complicated studies are continued: Blackburn and Millen (2012) focused on a mixed integer nonlinear programming (MINLP) model including raw material, WIP, and finished goods. Later Blackburn and Millen (2010) proposed a greedy heuristic algorithm based B&B Algorithm to optimize the model described in (Anderson, 2011). Other works that addressed the related issues are Betts and Johnston (2009); Blackburn and Millen (2011); Mulligan and Gordon (2014).

In a supply chain manufacturing system, the inventory control and the need for coordination of inventory decisions are important issues. One of the reasons why inventory is needed is to protect a firm from unexpected changes in customer demand that are always difficult to predict. In the recent decade, the uncertainty is even more difficult to predict due to the short life cycle of an increasing number of products and the presence of competing products in the market. Typically, the manufacturers order raw materials from outside suppliers to produce the finished products. Therefore, inventory types can be categorized into raw material inventory, WIP inventory and finished product inventory. Since holding of inventories cause a significant cost, their efficient management is critical in production and supply chain system operations. A system, which provides excess inventory, reflects lack of planning and poor communication and management. It has been an important issue to integrate inventories including raw materials, WIP, and finished products in the system for efficient production, distribution, and control tactics to reduce the inventory related cost of the system. A decision-making model is developed for an optimal set of production rates and raw materials procurement rate selection to minimize the total inventory cost incurred by raw materials, WIP, and finished products of Varying Production Rates and Demand (VPRD) model. This

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study also discusses the associated Kanban system’s configuration of the VPRD system. The formulations of the model depend on some assumptions and notations. They are described with the graphical illustrations below.

(a) On hand inventory of raw materials

(b) On hand inventory of work-in-process at the ithKanban stage

(c) On hand inventory of finished products

Figure 2.19 VPRD Production System Inventory Formations

57 Assumptions

The following assumptions are made to formulate the VPRD problem:

(1) Enough inventories exist and shortages never occur during production.

(2) The production rate is higher than the demand rate for all work-stages.

(3) The production of defective products is not considered.

(4) A one-to-one conversion ratio for the raw materials to finished products.

Notations

The notations used in this model are two kinds, (i) parameters, which are known and given values; (ii) variables, which are unknown. The objective of the VPRD problem is to determine the variables. The following parameters and variables will be used to formulate the problem or to interpret the results:

Parameters:

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59 Variables:

2.9.2.1 Optimal ordering policy for raw materials

Raw materials are required at the beginning of a production cycle. If the necessary raw materials are ordered once in a cycle, it may cause a higher inventory carrying cost during the earlier part of the production cycle. A multi-ordering policy which permits multiple ordering from outside suppliers of raw material in a production cycle may lower the inventory carrying cost as well as encourage the appropriate use of raw materials. Hence, raw material ordering policy regarding the optimal number of orders, time intervals of orders and ordering quantities are important factors of operational decisions.

2.9.2.2 Linear Demand of Finished Products

The concept of modeling with linear demand stated by Walleigh (2016) that the demand of a new product increases with time when it substitutes an existing product in most electronics, automobiles, and seasonal products which have short life in the competitive world market.

After saturation, the demand of this product remains approximately constant for a while until a new innovative product creeps into the market to dominate the existing product in terms of its capabilities and useful features. The existing product then starts experiencing the declining demand at this time. The varying demand can be approximated to a linear demand.

The advantage of modeling with linear demand is that it can analyze a manufacturing system with increasing, level and declining demand as it happens at the time of introduction of a new product, market maturity, and phasing out of the product, respectively. In a supply chain manufacturing system with JIT-Kanban mechanism, the output rate of the last stage is generally dictated by the demand of finished product from customers. The demand of a product is typically either increasing or decreasing or it remains constant over a certain period during its life cycle. It is observed that most short life-cycle products in the market such as

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electronics, automobiles, and other seasonal products get varying demand over their life cycles.