Flexible versus dedicated technology: A capacity expansion model

Over the past two decades, flexible manufacturing systems have been adopted in a variety of industries. Shorter product lives have necessitated acquiring flexible facilities. Further, the economies of scope that can be derived from producing products with different seasonality have made flexible facilities attractive. At the same time, dedicated facilities (such as transfer lines) have not disappeared because they offer economies of scale beneficial in high volume manufacturing environments. Hence, when producing a wide variety of products with different seasonality and demand growth rates, firms need to consider both economies of scale and economies of scope in deciding whether to acquire capacity of flexible or dedicated technology or both. In this paper, we consider the problem of making capacity acquisition decisions, when there is a choice of flexible and dedicated technologies available in a deterministic multi-product manufacturing environment with demand assumed to be nondeclining over time. We present a novel formulation of the problem and show the equivalence of the formulation to the uncapacitated plant location formulation. This enables us to use a very efficient solution procedure (Erlenkotter 1978) to solve even large problems optimally. We then present the results of an extensive computational study performed to evaluate the impact of key problem parameters on the proportion of flexible and dedicated capacity acquired. An interesting result of the study is that the proportion of flexible capacity acquired decreases with increasing scale economies. We also find that investment in flexible technology is significant even when it is relatively more expensive than dedicated technology.     

Multiobjective long-term planning of biopharmaceutical manufacturing facilities

Biopharmaceutical companies with large portfolios of clinical and commercial products typically need to allocate production across several multiproduct facilities, including third party contract manufacturers. This poses several capacity planning challenges which are further complicated by the need to satisfy different stakeholders often with conflicting objectives. This work addresses the question of how a biopharmaceutical manufacturer can make better long-term capacity planning decisions given multiple strategic criteria such as cost, risk, customer service level, and capacity utilization targets. A long-term planning model that allows for multiple facilities and accounts for multiple objectives via goal programming is developed. An industrial case study based on a large scale biopharmaceutical manufacturer is used to illustrate the functionality of the model. A single objective model is used to identify how best to use existing capacity so as to maximize profits for different demand scenarios. Mitigating risk due to unforeseen circumstances by including a dual facility constraint is shown to be a reasonable strategy at base case demand levels but unacceptable if demands are 150% higher than expected. The capacity analysis identifies where existing capacity fails to meet demands given the constraints. A multiobjective model is used to demonstrate how key performance measures change given different decision making policies where different weights are assigned to cost, customer service level, and utilization targets. The analysis demonstrates that a high profit can still be achieved while meeting key targets more closely. The sensitivity of the optimal solution to different limits on the targets is illustrated.     

Models for first-pass FMS investment analysis

Consider a firm that could choose either an inexpensive product-specific (dedicated) facility or a costly flexible facility, or a combination of the two, in order to satisfy demand for two product groups. Flexible technology offers benefits of scale and scope economies. However, it may have added operational costs due to the need to have excess capacity (to permit changeovers) and to maintain cycle stocks. As a consequence, the economic viability of flexible technology is significantly affected by the choice of the operating doctrine. This article presents first-pass decision models to help the firm choose the optimum sizes of facilities and the degree of flexibility for the flexible facility such that the contingent operational costs are simultaneously optimized. Two variations of the problem are considered. Whereas, the first applies to a situation in which the demand rates are constant and predictable, the second considers random demands. In each case, this study provides a formulation of the problem, structural results, and the sensitivity of the results to cost parameters. These results have modest data and computational requirements, making them suitable for first-cut attempts at narrowing available choices.     

Medium term planning of biopharmaceutical manufacture using mathematical programming

Regulatory pressures and capacity constraints are forcing the biopharmaceutical industry to consider employing multiproduct manufacturing facilities running on a campaign basis. The need for such flexible and cost-effective manufacture poses a significant challenge for planning and scheduling. This paper reviews the problem of planning and scheduling of biopharmaceutical manufacture and presents a methodology for the planning of multiproduct biopharmaceutical manufacturing facilities. The problem is formulated as a mixed integer linear program (MILP) to represent the relevant decisions required within the planning process and is tested on two typical biopharmaceutical industry planning problems. The proposed formulation is compared with an industrial rule based approach, which it outperforms in terms of profitability. The results indicate that the developed formulation offers an effective representation of the planning problem and would be a useful decision tool for manufacturers in the biopharmaceutical industry particularly at times of limited manufacturing capacity.     

Process flexibility and inventory flexibility via product substitution

This paper studies the optimal control of and interaction between two types of flexibility under Markov models of demand and production: process flexibility and inventory flexibility. In our model, process flexibility is generated by a multi-functional production facility that can produce two types of products, and inventory flexibility is manifested in firm-driven one-way product substitution. Both process flexibility and inventory flexibility are important drivers of supply chain performance and are strategic design considerations. To analyze the interaction between these two types of flexibility, we model a dynamically controlled two-product, make-to-stock system with stochastic processing times and stochastic demand. We characterize the complex joint optimal production and post-production policy for a special case and numerically show that a simply structured multi-threshold policy is a near-optimal heuristic policy for the general case. We gain further insight into the impact of system parameters on the value of process flexibility and inventory flexibility via a comprehensive numerical study. We find that for a wide range of capacity and cost parameters, process flexibility and inventory flexibility complement each other, so pursuing both forms of flexibility is effective.     

Capacity planning for batch and perfusion bioprocesses across multiple biopharmaceutical facilities

Production planning for biopharmaceutical portfolios becomes more complex when products switch between fed‐batch and continuous perfusion culture processes. This article describes the development of a discrete‐time mixed integer linear programming (MILP) model to optimize capacity plans for multiple biopharmaceutical products, with either batch or perfusion bioprocesses, across multiple facilities to meet quarterly demands. The model comprised specific features to account for products with fed‐batch or perfusion culture processes such as sequence‐dependent changeover times, continuous culture constraints, and decoupled upstream and downstream operations that permit independent scheduling of each. Strategic inventory levels were accounted for by applying cost penalties when they were not met. A rolling time horizon methodology was utilized in conjunction with the MILP model and was shown to obtain solutions with greater optimality in less computational time than the full‐scale model. The model was applied to an industrial case study to illustrate how the framework aids decisions regarding outsourcing capacity to third party manufacturers or building new facilities. The impact of variations on key parameters such as demand or titres on the optimal production plans and costs was captured. The analysis identified the critical ratio of in‐house to contract manufacturing organization (CMO) manufacturing costs that led the optimization results to favor building a future facility over using a CMO. The tool predicted that if titres were higher than expected then the optimal solution would allocate more production to in‐house facilities, where manufacturing costs were lower. Utilization graphs indicated when capacity expansion should be considered. © 2013 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 30:594–606, 2014     

A Dynamic Tool Requirement Planning Model for Flexible Manufacturing Systems

Despite their strategic potential, tool management issues in flexible manufacturing systems (FMSs) have received little attention in the literature. Nonavailability of tools in FMSs cuts at the very root of the strategic goals for which such systems are designed. Specifically, the capability of FMSs to economically produce customized products (flexibility of scope) in varying batch sizes (flexibility of volume) and delivering them on an accelerated schedule (market response time) is seriously hampered when required tools are not available at the time needed. On the other hand, excess inventory of tools in such systems represents a significant cost due to the expensive nature of FMS tool inventory. This article constructs a dynamic tool requirement planning (DTRP) model for an FMS tool planning operation that allows dynamic determination of the optimal tool replenishments at the beginning of each arbitrary, managerially convenient, discrete time period. The analysis presented in the article consists of two distinct phases: In the first phase, tool demand distributions are obtained using information from manufacturing production plans (such as master production schedule (MPS) and material requirement plans (MRP)) and general tool life distributions fitted on actual time-to-failure data. Significant computational reductions are obtained if the tool failure data follow a Weibull or Gamma distribution. In the second phase, results from classical dynamic inventory models are modified to obtain optimal tool replenishment policies that permit compliance with such FMS-specific constraints as limited tool storage capacity and part/tool service levels. An implementation plan is included.     

Models for capacity acquisition decisions considering operational costs

In this article, we study a capacity acquisition problem by considering technology choice and operational factors in a stochastic environment. The motivation for our work comes from developments in modern flexible technologies and a problem encountered in a real industrial setting. We study the impact of operational factors such as setup times, demand patterns, and inventory/back order costs on the decisions of capacity acquisition and technology choice. We consider three alternatives in capacity and technology decisions: (i) a flexible system, (ii) a dedicated system, and (iii) a combination of these two systems. For each system, we develop a model that integrates investment decisions and operational decisions to determine an optimal amount of capacity to purchase and the time and the types of parts to produce. The objective is to minimize the capacity acquisition cost at the beginning of the planning horizon and the total expected operational costs over an infinite planning horizon. To solve the problem in this article, a solution procedure is proposed. Managerial insights are also derived from extensive computational results.     

Environmental Impact of Public Charging Facilities for Electric Two‐Wheelers

The environmental characterization of the charging infrastructure required to operate electric vehicles (EVs) is usually overlooked in the literature. Only rudimentary life cycle inventories of EV charging facilities are available. This lack of information is especially noticeable in environmental studies of the environmental performance of electric two‐wheelers (E2Ws), none of which have included an analysis of charging facilities, even though they constitute the most successful electric‐drive market in the world. This article focuses on characterizing the life cycle of the global warming potential (GWP) and primary energy demand (PED) of two conventional charging facility designs that are widely implemented for charging E2Ws in public spaces. The relative environmental relevance of charging facilities per kilowatt‐hour (kWh) supplied to E2Ws is determined by considering a range of use scenarios (variability in the service ratio) and the effect of upgrading the electricity mix to include more renewable energy sources. Savings of over 3 metric tons (tonnes) of carbon dioxide equivalent emissions and 56 equivalent gigajoules can be achieved by implementing an optimized charging facility design. The internalization of the relative environmental burden from the charging facility per kWh supplied to E2Ws can increase the GWP of E2Ws’ use phase from 1% to 20% and the PED from 1% to 13%. Although the article focuses on one particular case scenario, the research is intended to provide complementary criteria for further research on the life cycle management of electric mobility systems. Thus, a series of factors that can influence the environmental performance of EV charging networks at the macro scale are discussed.     

Administrative gatekeeping - a third way between unrestricted patient advocacy and bedside rationing

The inevitable need for rationing of healthcare has apparently presented the medical profession with the dilemma of choosing the lesser of two evils. Physicians appear to be obliged to adopt either an implausible version of traditional professional ethics or an equally problematic ethics of bedside rationing. The former requires unrestricted advocacy of patients but prompts distrust, moral hazard and unfairness. The latter commits physicians to rationing at the bedside; but it is bound to introduce unfair inequalities among patients and lack of political accountability towards citizens. In this paper I shall argue that this dilemma is false, since a third intermediate alternative exists. This alternative, which I term 'administrative gatekeeping', makes it possible for physicians to be involved in rationing while at the same time being genuine advocates of their patients. According to this ideal, physicians are required to follow fair rules of rationing adopted at higher organizational levels within healthcare systems. At the same time, however, they are prohibited from including considerations of cost in their clinical decisions.     

Impact of contracted manufacturing organization protocols on operations in an aca demically based Current Good Manufacturing Practice facility

Immunotherapy of cancer and other diseases is often dependent on adoptive transfer to patients of cellular products generated in Current Good Manufacturing Practice (cGMP) facilities. With the availability and approval of various cellular products for therapy, cell production facilities are experiencing unprecedented growth in demand for services. Increasingly, these services involve processing of externally generated cells for transfer to the bedside. The arrival of cells from external manufacturing facilities for processing and eventual infusion of cell therapy products into patients creates a new layer of responsibility and adds to an already demanding list of the existing procedures in academic cGMP facilities. Sponsors introduce their own requirements for the handling of cells that the laboratory must incorporate and follow. The challenges of creating additional access to cleanrooms, writing new standard operating procedures, expanding personnel training, altering pre-existing schedules and incorporating additional monitoring for safety of external products alter the balance of laboratory operations. Adjustments for accommodating externally manufactured products are numerous and varied, as each sponsor has requests that are product-specific. If cells produced by several different external manufacturers are handled by the same facility, the negative impact on the regular activities in this facility may be considerable. Here the authors provide a review of operational challenges that an academic-based laboratory faces and discuss solutions that could ameliorate the difficulties related to an increasing volume of industry-sponsored trials. The solution may be the development under the auspices of the Foundation for Accreditation of Cellular Therapy or the Food and Drug Administration of regulations that will guide the processing of products manufactured by external companies and make these regulations broadly applicable in all cGMP facilities.     

Bacterial contaminants of fuel ethanol production

Bacterial contamination is an ongoing problem for commercial fuel ethanol production facilities. Both chronic and acute infections are of concern, due to the fact that bacteria compete with the ethanol-producing yeast for sugar substrates and micronutrients. Lactic acid levels often rise during bouts of contamination, suggesting that the most common contaminants are lactic acid bacteria. However, quantitative surveys of commercial corn-based fuel ethanol facilities are lacking. For this study, samples were collected from one wet mill and two dry grind fuel ethanol facilities over a 9 month period at strategic time points and locations along the production lines, and bacterial contaminants were isolated and identified. Contamination in the wet mill facility consistently reached 10⁶ bacteria/ml. Titers from dry grind facilities were more variable but often reached 10⁸/ml. Antibiotics were not used in the wet mill operation. One dry grind facility added antibiotic to the yeast propagation tank only, while the second facility dosed the fermentation with antibiotic every 4 h. Neither dosing procedure appeared to reliably reduce overall contamination, although the second facility showed less diversity among contaminants. Lactobacillus species were the most abundant isolates from all three plants, averaging 51, 38, and 77% of total isolates from the wet mill and the first and second dry grind facilities, respectively. Although populations varied over time, individual facilities tended to exhibit characteristic bacterial profiles, suggesting the occurrence of persistent endemic infections.Names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by USDA implies no approval of the product to the exclusion of others that may also be suitable.     

Assessing capacity scalability policies in RMS using system dynamics

This paper presents a model for assessing different capacity scalability policies in Reconfigurable Manufacturing System (RMS) for different changing demand scenarios. The novelty of this approach is two fold: (1) it is the first attempt to explore different capacity scalability policies in RMS based on multiple performance measures, mainly scaling rate, Work In Process level, inventory level and backlog level; and (2) the dynamic scalability process in RMS is modeled for the first time using System Dynamics. Different policies for capacity scalability for various demand scenarios were assessed. Numerical simulation results obtained using the developed capacity scalability model showed that the best capacity scalability policy to be adopted for RMS is dependent on the anticipated demand pattern as well as the various manufacturing objectives. The presented assessment results will help the capacity scalability planners better decide the different tradeoffs between the competing strategic and operational objectives of the manufacturing enterprise, before setting the suitable capacity scalability plan parameters.     

Impact of ramp-up on the optimal capacity-related reconfiguration policy

This paper presents an optimal solution, based on Markov decision theory, for the problem of optimal capacity-related reconfiguration of manufacturing systems, under stochastic market demand. Both capacity expansion and reduction are considered. The solution quantitatively takes into account the effect of the ramp-up phenomenon, following each reconfiguration, on the optimal policy. A closed-form solution is presented for when product demand is independently and generally distributed over time. A real case concerning a flexible manufacturing line in the automotive sector is shown, to prove that ignoring the ramp-up effect in the decision process can lead to significant increases in overall costs.     

Challenges for proteomics core facilities

Many analytical techniques have been executed by core facilities established within academic, pharmaceutical and other industrial institutions. The centralization of such facilities ensures a level of expertise and hardware which often cannot be supported by individual laboratories. The establishment of a core facility thus makes the technology available for multiple researchers in the same institution. Often, the services within the core facility are also opened out to researchers from other institutions, frequently with a fee being levied for the service provided. In the 1990s, with the onset of the age of genomics, there was an abundance of DNA analysis facilities, many of which have since disappeared from institutions and are now available through commercial sources. Ten years on, as proteomics was beginning to be utilized by many researchers, this technology found itself an ideal candidate for being placed within a core facility. We discuss what in our view are the daily challenges of proteomics core facilities. We also examine the potential unmet needs of the proteomics core facility that may also be applicable to proteomics laboratories which do not function as core facilities.     

Direct and Indirect Effects of Product Mix Characteristics on Capacity Management Decisions and Operating Performance

Studies of the performance effects of product mix complexity typically treat plant capacity utilization and machine scheduling (for example, setup frequency) as exogenous factors associated with technology choices, economies of scale, and the level of market demand. However, capacity utilization and machine scheduling also reflect tactical operating decisions taken by local managers to maximize short-run performance. If managers rationally anticipate a negative relation between performance and product mix complexity, we expect tactical operating decisions to be used to mitigate performance degradation. Previous empirical studies that ignore this simultaneity provide an incomplete assessment of the performance effects of product mix complexity. This paper uses path analysis to examine the combined impact of product mix on capacity management decisions and operating performance in three textile manufacturing plants. The results support the hypothesis that product mix acts through capacity management decisions to reduce performance from the level implied by direct effects alone. The evidence also supports the behavioral proposition that managers use capacity management decisions strategically—creating production slack when product mix is anticipated to most affect performance. However, although managers use discretionary capacity management intensively when the product mix is composed of complex, heterogeneous products, they are unable or unwilling to use these decisions to fully offset the performance impact of product mix.     

Monetary Valuation of Emissions in Implementing Environmental Policy

At various levels of environmental policy making there is a demand to translate polluting emissions into monetary units. In the so-called reduction cost approach, based upon policy targets, polluting emissions are expressed in monetary terms by determination of the marginal unit reduction cost at the emission target level. This approach provides shadow prices for emissions by which it can be established whether a certain measure or technology belongs to the most efficient set of measures by which the policy targets can be reached. This article argues that, if clear (generic) government targets such as national emission reduction targets exist for an emission, shadow prices derived by this method are to be preferred to shadow prices derived by other methods for decisions at the project (implementation) level. By application of the reduction cost approach, implementation decisions can be made that are both cost-effective and consistent with government policy.     

Evaluating the Impact of the Community-Based Health Planning and Services Initiative on Uptake of Skilled Birth Care in Ghana

Background

The Community-based Health Planning and Services (CHPS) initiative is a major government policy to improve maternal and child health and accelerate progress in the reduction of maternal mortality in Ghana. However, strategic intelligence on the impact of the initiative is lacking, given the persistant problems of patchy geographical access to care for rural women. This study investigates the impact of proximity to CHPS on facilitating uptake of skilled birth care in rural areas.

Methods and Findings

Data from the 2003 and 2008 Demographic and Health Survey, on 4,349 births from 463 rural communities were linked to georeferenced data on health facilities, CHPS and topographic data on national road-networks. Distance to nearest health facility and CHPS was computed using the closest facility functionality in ArcGIS 10.1. Multilevel logistic regression was used to examine the effect of proximity to health facilities and CHPS on use of skilled care at birth, adjusting for relevant predictors and clustering within communities. The results show that a substantial proportion of births continue to occur in communities more than 8 km from both health facilities and CHPS. Increases in uptake of skilled birth care are more pronounced where both health facilities and CHPS compounds are within 8 km, but not in communities within 8 km of CHPS but lack access to health facilities. Where both health facilities and CHPS are within 8 km, the odds of skilled birth care is 16% higher than where there is only a health facility within 8km.

Conclusion

Where CHPS compounds are set up near health facilities, there is improved access to care, demonstrating the facilitatory role of CHPS in stimulating access to better care at birth, in areas where health facilities are accessible.     

A Framework for Managing Core Facilities within the Research Enterprise

Core facilities represent increasingly important operational and strategic components of institutions'' research enterprises, especially in biomolecular science and engineering disciplines. With this realization, many research institutions are placing more attention on effectively managing core facilities within the research enterprise. A framework is presented for organizing the questions, challenges, and opportunities facing core facilities and the academic units and institutions in which they operate. This framework is intended to assist in guiding core facility management discussions in the context of a portfolio of facilities and within the overall institutional research enterprise.