Small Batch Manufacturing in the Age of Disruption to Reduce Slow Moving, Obsolete and Deteriorating Finished Goods in Fast Moving Consumer Goods Industry

The fast-moving consumer goods (FMCG) industry is characterised by many stock keeping units being held in hypermarkets, supermarkets, minimarkets, convenience stores, smaller sundry shops as well as in centralised or decentralised warehouses supplied from batch manufacturing. In the process of manufacturing and distributing a large range of items, a portion of slow-moving items result in obsolete stocks being held. These slow-moving items often sit on shelves for long periods of time and upon reaching their expiry dates, some deteriorate too. In these circumstances, the supply chain manager may decide to dispose or write them off at a loss. This study aims to show how analysis of such inventory and their demand popularity could be used to install small batch capacity, applying a make to order policy in the FMCG industry for non-popular items. Supply chain managers may also transfer finished goods and moving single units of finished goods from an opened carton between retail outlets and warehouses before applying a make when zero policy to reduce and eliminate such waste in supply chains

Finite capacity planning algorithm for semiconductor industry considering lots priority

International audienceA finite capacity planning heuristic is developed for semiconductor manufacturing with high-mix low-volume production, complex processes, variable cycle times and reentrant flows characteristics. The proposed algorithm projects production lots trajectories (start and end dates) for the remaining process steps, estimates the expected load for all machines and balances the workload against bottleneck tools capacities. It takes into account lots' priorities, cycle time variability and equipment saturation. This algorithm helps plant management to define feasible target production plans. It is programmed in java, and tested on real data instances from STMicroelectronics Crolles300 production plant which allowed its assessment on the effectiveness and efficiency. The evaluation demonstrates that the proposed heuristic outperforms current practices for capacity planning and opens new perspectives for the production line management

Cycle Time Analysis For Photolithography Tools In Semiconductor Manufacturing Industry With Simulation Model : A Case Study [TR940. S618 2008 f rb].

Perkembangan industri semikonduktor dalam bidang fabrikasi biasanya melibatkan kos pelaburan yang tinggi terutamanya dalam alatan photolithography. The industry of semiconductor wafer fabrication (“fab”) has invested a huge amount of capital on the manufacturing equipments particular in photolithograph

Single-site strategic capacity planning considering renewal, maintenance, inventory, taxes and cash flow management

This paper deals with strategic capacity planning of a single-site manufacturing system. We propose a MILP model that includes relevant business aspects and possibilities, some of which are only partially or not at all found in the literature. Specifically, we consider decisions on expansion, reduction and renewal of production capacity, and acquisition of storage capacity. In addition, we model aspects such as (a) maintenance costs and unit variable costs depending, respectively, on age and characteristics of facilities, (b) seasonality of the demand and (c) cash flow management, including taxes and, therefore, depreciation of assets. The model maximises the after-tax cash balance at the end of the planning horizon. We also present a computational experiment with 54 instances to show that the model can be solved for a wide range of sizes in a reasonable computing time using comercial software.Peer ReviewedPostprint (author's final draft

MEĐUOVISNOST ZASTUPLJENOSTI PROBLEMA U PLANIRANJU KAPACITETA I PROFITABILNOST I KONKURENTNOSTI PROIZVODNIH PODUZEĆA

U ovom radu provedeno je istraživanje o utjecaju stupnja zastupljenosti problema u planiranju kapaciteta na profitabilnost i konkurentnost na primjeru poduzeća strojogradnje. Rezultati istraživanja pokazali su da poduzeća koja imaju niži stupanj zastupljenosti problema u planiranju kapaciteta nemaju veću profitabilnost i konkurentnost od poduzeća s višim stupnjem zastupljenosti istih. Osim toga, rezultati istraživanja pokazali su da srednja poduzeća imaju nešto veću zastupljenost problema u planiranju kapaciteta od velikih, odnosno da nema značajne razlike između srednjih i velikih poduzeća s obzirom na stupanj zastupljenosti problema u planiranju kapaciteta. S druge strane, kada se analizira tip proizvodnog procesa rezultati su pokazali da između tipova proizvodnog procesa i stupnjeva zastupljenosti problema u planiranju kapaciteta postoji statistički značajna razlika čime se može prihvatiti tvrdnja da poduzeća koja imaju prekidani tip procesa imaju viši stupanj zastupljenosti problema u planiranju kapaciteta od poduzeća s linijskim i projektnim tipom procesa

High fidelity simulation models for equipment performance prediction in semiconductor industry

Semiconductor manufacturing is a high-technology industry which is capital intensive and operationally complex with its process technology refreshed every two years. Precision in capacity planning is critical to ensure the right amount of capital equipment is purchased to match the demand while meeting aggressive cost and operational targets. The key input parameter for capacity calculations is the equipment output rate. As equipment get more complex, its output rate become difficult to predict using spreadsheets, thus the need for detailed dynamic equipment simulation models. However, literature on how to build detailed equipment simulation models for real-world is scarce. Practitioners do not share their experience openly due to proprietary reasons. This dissertation investigates the complexity of semiconductor manufacturing which makes its capacity planning difficult. The techniques to build, verify and validate high fidelity equipment simulation models were developed. The models are then used to augment capacity planning and productivity improvement decision making. Case studies are conducted using the models to improve capacity forecast planning accuracy for capital purchase decisions which resulted in million dollars capital avoidance, test equipment productivity improvement ideas and decide which ones have benefits to pursue, and determine the effect of different operator manning ratios for manufacturing execution decisions. The results show that raw model accuracy can be up to 99% using the methods described here. For manufacturing execution, model accuracy can be up to 95% due to variability in human performance, but good enough to provide insights on manning ratio strategies. The case studies demonstrate how the results directly contribute to company performance in terms of capital efficiency, capital expenditure avoidance, and waste reduction. It enables optimal equipment configuration decisions to be made upfront during technology development. It also earns credibility and senior management confidence in using such simulation models for decision making

Cycle Time Analysis For Photolithography Tools In Semiconductor Manufacturing Industry With Simulation Model: A Case Study

Perkembangan industri semikonduktor dalam bidang fabrikasi biasanya melibatkan kos pelaburan yang tinggi terutamanya dalam alatan photolithography. Perkembangan pesat dalam bidang industri semikonduktor kini telah memerangsangkan teknik untuk mengoptimumkan penggunaan mesin-mesin dengan efektif setelah membelanjakan beribu juta dalam perlaburan. Tanpa penggunaan perisian komputer yang canggih dalam analisis, adalah sukar untuk menggunakan teknik purba dalam analisis pengiraan apabila menghadapi perkembangan produk yang semakin tinggi teknologinya. Dalam kajian ini, satu model simulasi telah dibina untuk menganalisis masa mendulu dalam alatan photolithography melalui teknik yang lebih sistematik dan efektif. Model simulasi ini telah dibina berasaskan perisian computer yang memerlukan informasi yang teliti seperti mas a memproses dan juga aliran proses dalam alatan photolithography. The industry of semiconductor wafer fabrication ("fab") has invested a huge amount of capital on the manufacturing equipments particular in photolithography area which has driven the needs to re-look at the most profitable way of utilizing and operating them efficiently. Traditional industrial engineering analysis techniques through mathematical models or static models for the studies of photolithography process are simply not adequate to analyze these complex environments. In this research, a more realistic representation of photolithography tools that can give a better prediction results and a more systematic methodology for minimizing photolithography cycle time is presented. The proposed method is to reduce waiting time and increase utilization of the photolithography process, which would result in an overall equipment cycle time reduction

Long term capacity planning with products' renewal

Long Term Capacity Planning (LTCP) consists of deciding the type and amount of capacity of production systems for multiple periods in a long term planning horizon. It involves decisions related to strategic planning, such as buying or selling of production technology, outsourcing, and making tactical decisions regarding capacity level and configuration. Making these kinds of decisions correctly is highly important for three reasons. Firstly, they usually involve a high investment; secondly, once a decision like this is taken, it cannot be changed easily (i.e. they are highly irreversible); thirdly, they affect the performance of the entire system and the decisions that will be possible at a tactical level. If capacity is suboptimal, there will be lost demand (in the present and possibly in the future); if the system is oversized, there will be unused resources, which may represent an economical loss. Long term decisions are typically solved with non-formalized procedures, such as generating and comparing solutions, which do not guarantee an optimal solution. In addition, the characteristics of the long term capacity planning problem make the problem very difficult to solve, especially in cases in which products have a short life cycle. One of the most relevant characteristics is the uncertainty inherent to strategic problems. In this case, uncertainty affects parameters such as demand, product life cycle, available production technology and the economic parameters involved (e.g. prices, costs, bank interests, etc.). Selection of production technology depends on the products being offered by the company, along with factors such as costs and productivity. When a product is renewed, the production technology may not be capable of producing it; or, if it can, the productivity and/or the quality may be poor. Furthermore, renewing a product will affect its demand (cannibalization), as well as the demand and value of the old products. Hence, it is very important to accurately decide the correct time for product renewal. This thesis aims to design a model for solving a long term capacity planning problem with the following main characteristics: (1) short-life cycle products and their renewal, with demand interactions (complementary and competitive products) considered; (2) different capacity options (such as acquisition, renewal, updating, outsourcing and reducing); and (3) tactical decisions (including integration strategic and tactical decisions)

Seleção de componentes eletrônicos durante o Processo de Desenvolvimento de Produtos de empresas brasileiras.

A eletrônica tem sido um dos pilares da inovação nos mais diversos setores industriais. Os avanços tecnológicos na miniaturização de componentes e as crescentes exigências dos clientes pressionam as empresas a desenvolverem seus produtos de forma mais eficiente. Dispositivos eletrônicos envolvem um dependente e interconectado conjunto de peças que solucionam as funções internas do produto, tornando sua atividade de seleção um item crucial para os desenvolvedores. Nesta atividade, a atenção aos lançamentos de novas tecnologias permite que as empresas permaneçam atualizadas em relação aos componentes disponíveis no mercado. Entretanto, no Brasil, o acesso a estes lançamentos pode ser comprometido devido à carência de fabricantes de componentes eletrônicos no país, forçando as empresas a dependerem de tecnologia externa para o desenvolvimento de seus produtos. O objetivo desta pesquisa é analisar os critérios utilizados, pelas empresas brasileiras, para a seleção de componentes eletrônicos no Processo de Desenvolvimento de Produtos (PDP), identificando as características que influenciam a atividade e os principais motivadores de alterações na lista de componentes (BOM) do produto após seu lançamento. Para isso, utilizou-se o método de pesquisa levantamento (survey) de caráter descritivo. A sistemática e o instrumento para coleta de dados propostos foram validados por meio de um teste piloto e aplicados a uma amostra aleatória de 75 empresas brasileiras desenvolvedoras de produtos eletrônicos. Os resultados do trabalho evidenciam uma maior importância dos critérios de seleção que consideram o ambiente do produto, atribuindo a atividade de qualificação do componente em si a seus fabricantes e distribuidores. Também apontam que a importância dada aos critérios é maior ao considerar componentes de maior valor agregado devido ao risco de reprojeto envolvido. Além disso, destaca-se que o maior motivador de alterações no BOM é a obsolescência de componentes, colocando-o como um fator crítico nas empresas estudadas

Tool capacity planning in semiconductor manufacturing

The demand for distinct wafer types in semiconductor manufacturing is an explicit function of the electronic components in which these wafers are used. Given that the component demands vary not only by the product type but also over time, it is obvious that wafer demands are also lumpy and time varying. In this paper, we discuss strategic level investment decisions on procuring new equipment and aggregate level capacity planning. In this context, we examine the problem of planning wafer production over multiple time periods within a single facility assuming that a demand forecast for each wafer type for each period is known. To address this problem, we develop a multi-period mixed integer programming model to minimize the machine tool operating costs, new tool acquizition costs, and inventory holding costs. Given that production of wafers requires a large number of operations with multiple tools capable of performing each operation, tool operating costs are explicitly minimized by integrating the assignment of specific operations to tools in our model. Since our model is computationally intractable, we propose a Lagrangean-based relaxation heuristic to find efficient tool procurement plans