Goal Programming - Computer Numerical Control Machines - Essay Example

Name: Professor’s Name: Course: Date: Goal Programming For business organizations to be successful managerial decisions requires to be made by the decision makers who are concerned in making decisions that are capable of simulating real life situations involving the organizational multiple objectives such as cost minimization that are naturally conflicting. One of the techniques used for such kinds of multi-objective optimization decisions to formulate the best available solution is Goal programming. Goal programming is a linear programming extension that can be defined as multi-objective optimization branch, with the multi-objective optimization been a part of multi-criteria decision analysis (MCDA) also called multi-criteria decision making (MCDM). The main purpose of this optimization programme is to handle normally conflicting multi-objective measures, every measure is provided with a goal to be fulfilled. An achievement function is then used to minimize the unwanted deviations from the set goals. Dependent on the used variant of goal programming, this can either be a weighted sum or vector. Goal programming conducts analysis of three types: (1) Establish the resources required in order to fulfil the wanted set of goals and objectives. (2) Determine the attainment degree of the set goals with the current resources available. (3) Providing the most fulfilling answer below the varying resources amount and goal priorities (Caballero, Rafael, Trinidad and Francisco, 79). Production planning is a no easy task and requires all the entire functional units’ cooperation in all organizations. For an efficient system of production planning, it is crucial to understand the organizations environment which includes customers, manufacturing processes and products. Good production planning in organizations is the key requirement for the success of a manufacturing system to address the limitations of flexibility and efficiency while considering the resource limitations such as time and labour (Olhager, Jan, and Joakim, 210). The production manager uses performance criteria as a guide for decision making. Multi-objective goal planning (MOGP) is the appropriate approach for handling this multi-level decision making process (Schniederjans, Marc, 10). Case Scenario Cosmos, the leading firm in the manufacturing industry of precision machine tools in India produces standardised, advanced and sophisticated machine tools. Cosmos consists of three divisions: machine tool, computer numerical control machines (CNC), forging and foundry. In the division of machine tools, the manufactured tools involve: milling machine, surface grinder, cutter and tool grinder and the thread-rolling machine of diverse models enclosing other versions of CNC. The company has over eight regional marketing offices all over India. Its sales forecasts for planning production were made, however, the current sales have surpassed the sales forecasted in some products and inferior in other certain products. I have been hired by the company to give an objective opinion and an achievable recommendation to the company, in order to be able to achieve this I have been gathering developments and timely information to assist me. Over the last few years the company has been running at a loss even if the performance of the company was satisfactory till then. The operating loss have been caused by a decrease in sales in many of the company’s products followed by production overheads increase. The main cause of decrease in sales of many products was the degree of competition in the industry. Currently the company has a labour force of 2000 employees with 60 percent of the labour force falling below the operator cadre that involves semi-skilled, unskilled and skilled workers. The main focus will be in the CNC division which produces CNC machining centres and CNC lathe of diverse models. In India the industry of engineering is still at the introductory stage of the CNC machines which are used in the industry of automobiles extensively both at the local and global level. When there is any significant increase in demand of CNC machine tools, the CNC production unit is forced to increase the production level. There are two numerical control machines in the CNC division (single slide way grinder and horizontal miller), horizontal boring and vertical miller CNC machines and a single conventional radial machine for drilling. The slide way grinding machines capacity provided by local sub-contractors was not available to meet the company’s requirements. The CNC division production manager also indicated that the machines capacity was the crucial and determining factor on the CNC division’s production capacity because the slide way grinding (SWG) machine is required for all the products parts. Overheads in the CNC machining centres were also observed been incurred. In order to fulfil the company’s overall objectives, The CNC division at its divisional level has also set its objectives which are: (1) Producing flexible and sophisticated precision machine tools both for local and global markets. (2) Been flexible enough to adapt to the changes in the design of the product in the market. (3) Improving production and reducing the costs of the products in order to maintain market share. (4) Enhancing customer satisfaction through the provision of products of high quality. The above stated objectives will be used to establish operational plans through a goal programming model to assess the trade-off in the product, customer and manufacturing process entities of the process of production planning. Multi-objectives Development The main challenges includes: production planning of CNC lathe and CNC machining centre with the use of existing available resources which constitute a crucial single SWG and four other machines that are not crucial. Severe competition, increasing product quality, customer satisfaction, avoiding SWG underutilization, operation on overtime of SWG in order to keep up employer to employee relations, quality costs, maximization of the company’s sales gross margin, minimization of production overheads and inventory costs of WIP. The performance criteria incorporated in the MOGP model include: (1) quality cost; (2) production cost; (3) each products production volume; (4) utilization of SWG; (5) sales revenue; (6) work-in-process inventory cost (Gandibleux, Xavier, ed, 6). The following is the formulation of the above stated criteria. Quality costs minimization, QC =………………………… (1) Production costs minimization, C = ………………………… (2) Product volume maximization, V = , for all i……………………. (3) Utilization of SWG, U = …………………………... (4) Sales revenue maximization, SR = …………………………. (5) Work-in-process inventory cost, W = ………………………….. (6) System constraints, ≤, for all j…………… (7) Goal programming model formulation Product quality: customer goal minimize () subject to + = 0 Market goal, minimize ( +) subject to += Manufacturer’s goal: sales revenue, minimize ( subject to Manufacturer’s goal: production cost, minimize () subject to Manufacturer’s goal: utilization of SWG, minimize () subject to Manufacturer’s goal: work-in-process inventory cost, minimize ( subject to Where; i = Product type (i = 1, 2 … n) j = machine type (non-crucial) (j = 1, 2... m) = SWG machine capacity needed to process product i = Cost of production of the i th product = Capacity needed for the i product from j th non-crucial machine = Incurred quality costs on the i th product = Sales revenue from i th product = Cost of work-in-process inventory cost joined with i th product = Entire capacity available of the j th non-crucial resource. Decision variable = Number of machines production volume of type i to be produced per period. Sensitivity Analysis of Goal Priority Structure Changes When testing the above formulated Goal programming model, two goal priorities are hierarchically represented reflecting top management decision preferences as shown below. Entity Goal Priority structure #1 #2 Goal deviations optimized Customer Quality Product Product 1 volume (V1) Product 2 volume (V2) Manufacturing process Sales revenue Production cost Utilization of SWG WIP inventory Where; Priority Structure #1 Priority 1: Achieve product1 and product2 demand goal Priority 2: Achieve customers quality goal Priority 3: Achieve goals of manufacturing process Priority Structure #2 Priority 1: Achieve product2 demand goal Priority 2: Achieve the product1 demand and manufacturing process goals Priority 3: Achieve customers quality goal Priority Goal structure #1 is the highest priority first assigned by management for the achievement of the product demand. The positive and negative deviations of product 1 and two demand need to be minimized.= refers to the second factor of the highest priority that is allocated to the minimizing of quality cost goal over achievement to fulfil the quality requirements of the customers). = represents the last priority factor allocated to the goals of the manufacturing process for the purpose of minimizing sales revenue under achievement (), minimizing the cost of production over achievement (), minimizing the SWG machine underutilization () and minimizing the WIP inventory over achievement (). The objective of this priority structure is to minimize goal deviations brought by the production environment. The variable that deviates and is joined to should be, to the most possible extent be minimized. Testing of the MOGP model was done using the data from the company records. Sample data was provided for each of the two pre-emptive priority structures. The two priority structures were then executed by the use of LINGO software package with the priorities having distinct values (Tamiz, Mehrdad, Dylan, and Carlos, 569). Goal priority structure sensitivity analysis was conducted for distinct associations of uncertain product demands indicated by the marketing division of the company. The goal priority structure #1 after the analysis was ruled to be the best recommendation that could be given to the company’s management to adapt in the production planning process in order to solve the current problem facing the company. In order to implement the recommended MOGP solution in priority structure #1, the marketing department requires to supply CNC lathe and CNC machining centre to the respective customers in reference to the optimum production volumes as explained by the ‘s resulting from the models. However, marketing conditions are beyond a company’s control and are bound to change in the long run forcing the company to restructure its goals in order to be able to adapt to the changing marketing environment. In the course of restructuring its goals the company can adopt the goal priority structure #2 as its strategy. When the company chooses to employ the full capacity of SWG and permit the machines operation on extra time in some occasions, it has to achieve the prescribed‘s. In such a case, the obtainable associated costs and sales revenue will be greater that the set targets. The goals attained by the priority structure #1 signify that the company is capable of achieving marketing goals and avoiding the SWG underutilization over a year. The optimum solution is not to experience product shortages and good SWG capacity utilization through overtime operation scheduling where applicable. Through this, the proposed MOGP model results will function a communication tool among the various departmental heads of the functional units in the company leading to increased productivity. Works Cited Caballero, Rafael, Trinidad Gómez, and Francisco Ruiz. "Goal programming: realistic targets for the near future." Journal of Multi‐Criteria Decision Analysis 16.3‐4 (2009): 79-110. Gandibleux, Xavier, ed. Multiple criteria optimization: state of the art annotated bibliographic surveys. Vol. 52. Springer Science & Business Media, 2006. Olhager, Jan, and Joakim Wikner. "Production planning and control tools." Production Planning & Control 11.3 (2000): 210-222. Schniederjans, Marc. Goal Programming: Methodology and Applications: Methodology and Applications. Springer Science & Business Media, 2012. Tamiz, Mehrdad, Dylan Jones, and Carlos Romero. "Goal programming for decision making: An overview of the current state-of-the-art." European Journal of operational research 111.3 (1998): 569-581. Read More