material planning in production
842120
Better workflow modelling of production processes: re engineering enterprise, resource and material planning in computational logistics
This paper examines standard methods for work and production flow modelling, and find that in some regards they are fundamentally being naive and erroneous. They simplify and "flatten" too much of the reality that they represent and allow much more than they can afford when it comes to using them for organizational re design. The problem is exacerbated when computational handling is considered. In this paper we illustrate the shortcoming with two industrial case studies, which we have approached ethnographically and through workshops.
CompSysTech '15
Steinar Kristoffersen
219129244
MATERIAL PLANNING AND SUPPLY MANAGEMENT SYSTEM FOR PRODUCTION INDUSTRIES
In production network the executives (SCM) two subjects have picked up significance in the course of the most recent years. From one viewpoint, reasonable SCM (SSCM) has become progressively important and numerous productions have contributed to the subject. Then again, data innovation (IT) is being continuously considered as a key empowering influence for productivity in supply chains. A few explore Endeavour have added to the field of IT for SSCM. The examination recognizes explore shortages just as an absence of logical talk utilizing exact methods and an absence of examinations on the social maintainability. Moreover, potential points for further explore were determined by contrasting the overview's outcomes with the ebb and flow inquire about on IT for 'general' SCM following the examination of 631 articles. Six fields could be distinguished, to be specific yield/impacts of IT, machine correspondence and multi agents, inputs furthermore, IT bolstered handling, ITempowered inter organizational trade, quantitative IT draws near and an area center.
Nithin S K Likith Naik S Rahul B Padmaja S K Dr Sumithra Devi K
113717508
Design and Building Information System of Raw Material Planning and Production Using Material Requirement Planning Method at Furniture Company
In fulfilling orders for subscriptions companies must improve performance in terms of planning. So far the problem in CV. Azaria Abadi Permai is planning needs raw materials and production is still in expected and done manually by the passage production planning inventory control. In this case often happens miscalculation planning raw needs an impact on exactly the number and availability of the raw materials that it production process. Solution proposed for the completion of the problems in the top is using methods Material Requirement Planning. This method aims to count the needs of raw materials and the arrival buy raw materials used the results of the evaluation of three lot sizing the technique, Lot for Lot, Economic Order Quantity, and Period Order Quantity. The result of this research is able to analyze method lot sizing namely, Lot for Lot, Economic Order Quantity, Period Order Quantity and then to choose the cost of inventori the most economical in each this method.
Daniel F Kale Henry Bambang Setyawan Erwin Sutomo
54753825
A Material Flow Modelling Tool for Resource Efficient Production Planning in Multi product Manufacturing Systems
Abstract Resource efficiency is recognized as one of the greatest sustainability challenges facing the manufacturing industry in the future. Materials are a resource of primary importance, making a significant contribution to the economic costs and environmental impacts of production. During the manufacturing phase the majority of resource efficiency initiatives and management methodologies have been concerned primarily with improvements measured on an economic basis. More recently, the need for even greater levels of resource efficiency has extended the scope of these initiatives to consider complete manufacturing and industrial systems at an economic and environmental level. The flow of materials at each system level relates directly to material efficiency, which in turn influences the consumption of other resources such as water and energy. Initial research by the authors in material efficiency focused on material flow, proposing a material flow assessment approach, comprising a systematic framework for the analysis of quantitative and qualitative flow in manufacturing systems. The framework was designed to provide greater understanding of material flow through identification of strengths, weaknesses, constraints and opportunities for improvement, facilitating the implementation of improvement measures for greater efficiency in both environmental and economic terms. This paper presents an extension of this work, applying the material flow assessment framework to a complex multi product and multi site manufacturing system scenario. It begins with a description of the Resource Efficient Scheduling (RES) tool that supports the implementation of this framework. The tool models the interactions of quantitative and qualitative material flow factors associated with production planning and the resulting impacts on resource efficiency. This provides a more detailed understanding of the economic and resource impacts of different production plans, enabling greater flexibility and the ability to make better informed decisions. Finally a case study is presented, highlighting the application of the tool and its potential benefits.
Oliver Gould Alessandro Simeone James Colwill R G Willey Shahin Rahimifard
28692987
A project scheduling approach to production and material requirement planning in Manufacturing to Order environments
Long and medium term production planning are tools to match production orders with resource capacity and that can also be used as a baseline for material procurement. The lack of a detailed schedule for the manufacturing operations, however, may cause difficulties in providing a proper material requirements planning and may affect the feasibility of the production plan itself. This paper proposes an approach, based on production process knowledge, to extract scheduling information from an aggregate production plan in order to support material procurement. The proposed approach is applied to an industrial case involving machining center production.
J. Intell. Manuf.
Arianna Alfieri Tullio Tolio Marcello Urgo
3080762
Modeling Cycle Times in Production Planning Models for Wafer Fabrication
A key parameter of the linear programming (LP) models widely used for production planning in industry and academia are the lead times, the estimated delay between material becoming available to a resource and its completion at that resource. Lead times are commonly treated as exogenous, workload independent parameters and assumed to be integer multiples of the planning period. Although formulations with non integer lead times have been implemented in industry, we are unaware of any studies systematically evaluating their performance. In this paper, we compare the performance of LP models with and without non integer lead times by simulating the execution of the resulting release plans. We also compare their performance to that of a formulation incorporating workload dependent lead times using nonlinear clearing functions. We find that the performance of the models with non integer lead times is substantially better than those with integer lead times, and often superior to that of the much more complex clearing function models. These results suggest that whenever reasonable estimates of the lead times are available, non integer lead times should be used due to their simplicity of implementation and excellent performance.
IEEE Transactions on Semiconductor Manufacturing
Necip Baris Kacar Lars Monch Reha Uzsoy
32613433
Production planning in additive manufacturing and 3D printing
Production planning problem in additive manufacturing and 3D printing is introduced.The mathematical model of the problem is developed and coded in CPLEX.Two heuristics are proposed and explained through a numerical example.Optimal and heuristic solutions are provided for the newly generated test problems.Experimental tests exhibit the requirement of planning in additive manufacturing. Additive manufacturing is a new and emerging technology and has been shown to be the future of manufacturing systems. Because of the high purchasing and processing costs of additive manufacturing machines, the planning and scheduling of parts to be processed on these machines play a vital role in reducing operational costs, providing service to customers with less price and increasing the profitability of companies which provide such services. However, this topic has not yet been studied in the literature, although cost functions have been developed to calculate the average production cost per volume of material for additive manufacturing machines.In an environment where there are machines with different specifications (i.e. production time and cost per volume of material, processing time per unit height, set up time, maximum supported area and height, etc. and parts in different heights, areas and volumes, allocation of parts to machines in different sets or groups to minimize the average production cost per volume of material constitutes an interesting and challenging research problem. This paper defines the problem for the first time in the literature and proposes a mathematical model to formulate it. The mathematical model is coded in CPLEX and two different heuristic procedures, namely best fit and adapted best fit rules, are developed in JavaScript. Solution building mechanisms of the proposed heuristics are explained stepwise through examples. A numerical example is also given, for which an optimum solution and heuristic solutions are provided in detail, for illustration. Test problems are created and a comprehensive experimental study is conducted to test the performance of the heuristics. Experimental tests indicate that both heuristics provide promising results. The necessity of planning additive manufacturing machines in reducing processing costs is also verified. Display Omitted
Comput. Oper. Res.
Qiang Li Ibrahim Kucukkoc David Zhengwen Zhang
154875789
Critical material planning for TFT LCD production industry
This research focuses on the material planning problem in the thin film transistor liquid crystal display (TFT LCD) manufacturing industry. With the growth in TFT LCD display applications, TFT LCD manufacturing has become the new high technology industry after semiconductor manufacturing. The final process of the TFT LCD industry, the module process, is a material oriented assembly production system that fabricates the panels produced from the preceding process and critical materials such as integrated circuit (IC) printed circuit board (PCB) and backlight (BL) into customized TFT LCD products according to different customer requirements. In addition, there are many specific characteristics such as alternative bill of material (ABOM) customer preference for ABOM, and purchase quantity ratio occurring in the TFT LCD industry. However, because of the uniqueness of the TFT LCD industry, material planning called critical material planning (CMP) must use a feasible and optimal purchase plan under these specific characteristics and constraints; also, the traditional material requirement planning (MRP) mechanism is no longer enough to deal with its planning problems. In response to this challenge, the current paper formulates a single period and multi period CMP problem as nonlinear programming models represented by the network graph. The purpose of this is to optimize the purchase quantity from suppliers while satisfying demand under the existence of specific characteristics. Additionally, we illustrate a numerical example from a real TFT LCD manufacturer to clarify the multi period CMP model; the managerial implications of the customer preference factors and the purchase quantity ratio are also correspondingly discussed.
James T Lin Tzu-Li Chen Yen-Ting Lin
111055513
Demand forecasting for production planning in remanufacturing
Remanufacturing is effective for energy and material savings; however, production planning and control in remanufacturing are more complex than those in traditional manufacturing. Developing a reliable forecasting method is critical for facilitating effective production planning and control. This study examined the effectiveness of demand forecasting in remanufacturing by time series analysis. Most existing methods of demand forecasting in remanufacturing assume that the time distributions of new product sales are known and that the time distributions of the demands of remanufactured products are determined by adding the product lifespan to the time distribution of new product sales. In addition, most previous studies focused on relatively long term demand trends without considering the seasonality of demands. In this study, we examined the Holt Winters model and the autoregressive integrated moving average (ARIMA) model, both representative time series analysis methods. These methods do not require information regarding the time distributions of new product sales and can handle the seasonality of demands. To examine the effectiveness of these methods, the time series data of the sales of 160 types of remanufactured alternators and starters manufactured by an independent auto parts remanufacturer over a period of 12 years was used. The results of demand forecasting for 2 months yielded average errors of 26.7 for alternators and 18.4 for starters, which represent an average improvement of 6.5 points compared to the method involving referencing the demands of the same month of previous year. The implications of the results and future steps are also discussed.
Mitsutaka Matsumoto Shingo Komatsu
165108641
Optimization of process planning for reducing material waste in extrusion based additive manufacturing
Abstract Among the available additive manufacturing technologies, extrusion based 3D printing (otherwise known as fused deposition modelling or fused filament fabrication) is among the most commonly used due to low cost and relative simplicity. However, such printers still suffer from redundant support material waste (both interior and exterior) when printing large volume solid objects or objects with overhangs. The support material can also be a significant cause of long part production time and higher energy consumption during manufacture. Hence, we propose a new support generation strategy considering both interior and exterior support via AM process planning to reduce the total amount of material consumption, production time and energy consumed for manufacturing an object. Print path and print orientation are both considered as significant factors and are both optimized for achieving the lowest consumption of material. The areas to be filled on each layer are determined according to the printable threshold overhang angle (PTOA) and the longest printable bridge length (LPBL) The characteristics of LPBL and PTOA are fully considered for saving more material. Several tests are used to verify the proposed strategy and the results show that this strategy can considerably reduce material waste, production time and energy consumed compared with conventional strategies, enabling AM to be a more environmentally friendly and sustainable manufacturing technique.
Robotics Comput. Integr. Manuf.
Jingchao Jiang Xun William Xu Jonathan Stringer