The authors focus on planning and control methods as they critically influence the production and business activities of any company. Under these conditions, Enterprise Resource Planning (ERP) acquires the top priority as an effective system allowing to perform these tasks (Cheng & Xiao-Bing, 2013). The article aims at discussing the model and outlining the defects it has. Another purpose of the paper is to propose a multi-objective production planning optimization model vital for attaining better outcomes (Cheng & Xiao-Bing, 2013). It also involves approaches for optimizing and controlling enterprise manufacturing management and improving results Altogether, the study discusses the practical value and applicability of the proposed model and its relevance.
The authors focus on planning and control methods as they critically influence the production and business activities of any company. Under these conditions, Enterprise Resource Planning (ERP) acquires the top priority as an effective system allowing to perform these tasks. The article aims at discussing the model and outlining the defects it has. Another purpose of the paper is to propose a multi-objective production planning optimization model vital for attaining better outcomes. It also involves approaches for optimizing and controlling enterprise manufacturing management and attaining improved outcomes. Altogether, the study discusses the practical value and applicability of the proposed model and its relevance.
At the moment, most enterprises use ERP to attain better outcomes and ensure the stable functioning of the unit. The authors offer the graphical representation of the model demonstrating stages needed to achieve desired goals (see Figure 1). However, there are still some disadvantages of the model, such as the lack of optimization mechanism, disconnection between material demand planning and capacity demand planning, consideration of only material and capacity (Cheng & Xiao-Bing, 2013). They result in the inability to create effective plans in some situations and succeed.
Method and Study Design
The study design presupposes the discussion of the ERP model regarding the information acquired from the literature review to outline its defects and understand how they can be eliminated. For this reason, the current management objectives are used as determinants of the approach’s effectiveness. The authors investigate a proposed optimized model regarding its scope, production balance, inventory, production, and demand. Employing this method, they manage to prove the improved applicability of a new framework and justify its further use and implementation in various situations. The study’s design also presupposes verifying the validity of the model by discussing its benefits and how it can be used in different scenarios.
Optimization Model Overview
The proposed optimization model based on multiple objectives focuses on the idea of forecasting and ordering data to generate the production demand planning, and regarding the existing inventory and safety inventory generate net product demand planning (Cheng & Xiao-Bing, 2013). It is expected that the given approach will result in the increased flexibility and better outcomes. The framework also presupposes that some stages can be repeated to attain the desired result and ensure that all variables and considered and used for effective planning. The model allows better resource and production planning and the effective use of resources (Cheng & Xiao-Bing, 2013). At the same time, it devotes more attention to multiple objectives, which is vital regarding the current sophistication of processes and their importance of a unit.
Any effective ERP model should presuppose the effective planning and forecasting function allowing managers to control the work of an enterprise. For this reason, the proposed optimized model helps to solve several problems linked to this sphere (Cheng & Xiao-Bing, 2013). First, planning shall meet the capacity demand to improve the work of units (Cheng & Xiao-Bing, 2013). Second, production planning can be optimized using such objectives as delivery, balanced production, inventory, and overtime production (Cheng & Xiao-Bing, 2013). Finally, material demand planning will result from enhanced production planning (Cheng & Xiao-Bing, 2013). Under these conditions, the authors assume that following the given model, it is possible to improve the planning function and create the basis for the future growth of the organization and its empowerment.
Product Demand Planning
The authors define product demand planning as the forecast and arrangements for the product demands in the future peculiar to a particular market (Cheng & Xiao-Bing, 2013). It usually rests on various factors, such as historic sales, future development of the market, and alterations in demand. From another perspective, received orders can also serve as the source for planning the product demand. That is why the final confirmation rests on orders, forecasts, or both of these elements. Because data coming from orders is reliable and credible, the offset relations between these orders and forecast can be determined by using the following formulae.
Net Product Demand Planning
Net product demand planning is another critical aspect that should be considered by planning models to ensure effective forecasting and to create the basis for the future work of organizations. The authors state that net product demand rests on product demand planning and consideration of the future and safety inventories (Cheng & Xiao-Bing, 2013). The following formula is offered by authors to determine the net product demand and use it in various models.
Available Capacity Planning
Available capacity planning is another vital element of the proposed model. It is based on the changes between the relevant capacity and the forecast capacity (Cheng & Xiao-Bing, 2013). The authors state that this factor is indicated by the product quantity playing a central role in the given model (Cheng & Xiao-Bing, 2013). The researchers also suggest the formula that helps to consider available capacity under both regular production situation and overtime production (Cheng & Xiao-Bing, 2013). Following the proposed model, if the regular production capacity has the desired showings, overtime production cannot be recommended because of high expenses and quality problems.
Multi-Objective Product Production Planning
Discussing the multi-objective product production planning, the authors also focus on the four central objectives peculiar to this framework. These include in-time delivery, production equilibrium, occupied inventory, and overtime production (Cheng & Xiao-Bing, 2013). These four aspects are vital for the effective planning and the correct functioning of any enterprise. Thus, offering formulas for processing and determining these showings, the researchers also emphasize how they can be integrated into real-life conditions to establish the correct course and avoid failures.
Because the previous model is viewed as the multi-objective one, it is possible to transform it and narrow the focus on a single goal to attain better planning and analysis of the current situation. The four objectives are interdependent and should be considered during the optimization process. The researchers assume that by setting the parameters of the four goals of cost, they can convert it into a single objective model with the parameters influencing the decision-making process (Cheng & Xiao-Bing, 2013). The offered formula helps to understand how to apply the framework and calculate the demanded outcomes.
The applicability and relevance of the authors’ assumptions are proven by the real-life example involving the company producing LCD and having the need to consider existing managerial objectives and follow the guidelines (Cheng & Xiao-Bing, 2013). Under these conditions, using the proposed optimization models, the researchers prove that its employment is beneficial to meet all demands and contribute to the better work of a unit.
Altogether, the paper proves that using a multi-objective optimization model, managers can improve their planning and attain better results. It is vital to consider performance management objectives and use specific cost parameters to control the manufacturing process and avoid failures. Proposing an improved model, the authors offer new options for more effective planning and the ability to influence the process in various ways.
Cheng, W., & Xiao-Bing, L. (2013). Integrated production planning and control: A multi-objective optimization model. Journal of Industrial Engineering and Management, 6(4), 815-830. Web.