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.     

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.     

Analysis of flexibility with rationing for a mix of manufacturing facilities

A major competitive advantage of a flexible manufacturing facility is its ability to cope with uncertainties in demand. At a strategic level, capacity-size decisions for a mix of flexible facilities (each not necessarily producing the same combination of products) are made based on aggregates of product types. Such an approach overlooks possible capacity-devouring by some products, arising at the operational level, when the aggregate demand for the period exceeds the available capacity. A rationing policy is required to ensure that the available aggregate capacity of the facilities is shared equitably. In this article, it is shown that such a rationing policy has an impact on the required capacity size and, therefore, must be integrated with the decisions at the strategic level. Several properties indicating the relative preferences of certain facility strategies are also established.     

The ecology of birth seasonality among agriculturalists in central Africa.

The Lese are subsistence farmers living in the Ituri Forest of north-east Za?re. They exhibit significant birth seasonality, with lowest frequencies of conception when food production is least, nutritional status is low and ovarian function, as measured by salivary steroid hormone levels, is reduced. Efe pygmy foragers, who live in the same geographical area but are less dependent on cultivated foods and have a more flexible life style, do not exhibit frequent fluctuations in nutritional status nor significant birth seasonality. These findings support a model of birth seasonality relating climatic variables to variation in fertility through a causal chain linking rainfall to food production to energy balance to ovarian function to fertility. The model, which emphasises an ecological approach to the study of human reproduction, should have broad applicability since seasonality of food production and energy balance is widespread geographically and across a wide variety of economies and cultures.     

Management of product variety in cellular manufacturing systems

In today’s markets, non-uniform, customized products complicate the manufacturing processes significantly. In this paper, we propose a cellular manufacturing system design model to manage product variety by integrating with the technology selection decision. The proposed model determines the product families and machine groups while deciding the technology of each cell individually. Hedging against changing market dynamics leads us to the use of flexible machining systems and dedicated manufacturing systems at the same facility. In order to integrate the market characteristics in our model, we proposed a new cost function. Further, we modified a well known similarity measure in order to handle the operational capability of the available technology. In the paper, our hybrid technology approach is presented via a multi-objective mathematical model. A filtered-beam based local search heuristic is proposed to solve the problem efficiently. We compare the proposed approach with a dedicated technology model and showed that the improvement with the proposed hybrid technology approach is greater than 100% in unstable markets requiring high product varieties, regardless of the volumes of the products.     

Production Capacity of Flexible Manufacturing Systems with Fixed Production Ratios

Determining the production capacity of flexible manufacturing systems is a very important issue in the design of such systems. We propose an approach for determining the production capacity (i.e., the maximum production rate) of a flexible manufacturing system with several part types, dedicated pallets, and fixed production ratios among the different part types. We show that the problem reduces to the determination of a single parameter for which we propose an iterative procedure. Simulation or approximate analytical techniques can be used as the building block performance evaluation technique in the iterative procedure.     

Single pass tangential flow filtration to debottleneck downstream processing for therapeutic antibody production

As the therapeutic monoclonal antibody (mAb) market continues to grow, optimizing production processes is becoming more critical in improving efficiencies and reducing cost-of-goods in large-scale production. With the recent trends of increasing cell culture titers from upstream process improvements, downstream capacity has become the bottleneck in many existing manufacturing facilities. Single Pass Tangential Flow Filtration (SPTFF) is an emerging technology, which is potentially useful in debottlenecking downstream capacity, especially when the pool tank size is a limiting factor. It can be integrated as part of an existing purification process, after a column chromatography step or a filtration step, without introducing a new unit operation. In this study, SPTFF technology was systematically evaluated for reducing process intermediate volumes from 2× to 10× with multiple mAbs and the impact of SPTFF on product quality, and process yield was analyzed. Finally, the potential fit into the typical 3-column industry platform antibody purification process and its implementation in a commercial scale manufacturing facility were also evaluated. Our data indicate that using SPTFF to concentrate protein pools is a simple, flexible, and robust operation, which can be implemented at various scales to improve antibody purification process capacity.     

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.     

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.     

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     

Near optimal manufacturing flow controller design

Flow control of flexible manufacturing systems (FMSs) addresses an important real-time scheduling requirement of modern manufacturing facilities, which are prone to failures and other controllable or stochastic discrete events affecting production capacity, such as change of setup and maintenance scheduling. Flow controllers are useful both in the coordination of interconnected flexible manufacturing cells through distributed scheduling policies and in the hierarchical decomposition of the planning and scheduling problem of complex manufacturing systems. Optimal flow-control policies are hedging-point policies characterized by a generally intractable system of stochastic partial differential equations. This article proposes a near optimal controller whose design is computationally feasible for realistic-size systems. The design exploits a decomposition of the multiple-part-type problem to many analytically tractable one-part-type problems. The decomposition is achieved by replacing the polyhedra production capacity sets with inscribed hypercubes. Stationary marginal densities of state variables are computed iteratively for successive trial controller designs until the best inscribed hypercubes and the associated optimal hedging points are determined. Computational results are presented for an illustrative example of a failureprone FMS.     

A knowledge-based system for the strategic control level of robots in flexible manufacturing cells

The strategic control level synthesis for robots is related to a hierarchical robot control problem. The main control problem at the strategic control level is to select the model and algorithm to be used by the lower control level to execute the given robot task. Usually there are several lower control level models and algorithms that can be used by the robot control system for every robot task. Strategic control level synthesis depends on the particular robot system application. In a typical application, when the robot system is used in a flexible manufacturing system for manipulating various part types, the robot tasks executed by the robot system depend on the manufacturing processes in the system. If the robot system is applied in another flexible manufacturing system, dedicated to other manufacturing processes, another set of robot tasks might be needed to perform the necessary operations. Therefore, the quantity and the kind of knowledge required in the system for the strategic control level differ from one application to another. Such a fact creates the appropriate conditions for employing some artificial intelligence techniques. This article describes a knowledge-based system approach to the strategic control level synthesis problem.     

Component Partitioning Under Demand and Capacity Uncertainty in Printed Circuit Board Assembly

This paper considers the problem of configuring a printed circuit board (PCB) assembly line experiencing uncertainty in demand and capacity. The PCB assembly process involves a single line of automatic placement machines, a variety of board types, and a number of component types. The line is set up only once, at the beginning of a production cycle, to eliminate setups between board types. Using this strategy, the line therefore can assemble all different types of PCBs without feeder changes. The problem then becomes to partition component types to the different machines in the hope of processing all boards quickly with a good workload balance. In this paper, the board demands and machine breakdowns are random but follow some probability distribution, which can be predicted from past observations of the system. We formulate this problem as a stochastic mixed-integer programming formulation with the objective of minimizing the expected makespan for assembling all PCBs during a production cycle. The results obtained indicate significant improvement over the existing methods. We hope that this research will provide more PCB assembly facilities with models and techniques to hedge against variable forecasts and capacity plans     

Comparison between centralized and decentralized supply chains of autologous chimeric antigen receptor T-cell therapies: a UK case study based on discrete event simulation

Background aimsDecentralized, or distributed, manufacturing that takes place close to the point of care has been a manufacturing paradigm of heightened interest within the cell therapy domain because of the product's being living cell material as well as the need for a highly monitored and temperature-controlled supply chain that has the potential to benefit from close proximity between manufacturing and application.MethodsTo compare the operational feasibility and cost implications of manufacturing autologous chimeric antigen receptor T (CAR T)-cell products between centralized and decentralized schemes, a discrete event simulation model was built using ExtendSIM 9 for simulating the patient-to-patient supply chain, from the collection of patient cells to the final administration of CAR T therapy in hospitals. Simulations were carried out for hypothetical systems in the UK using three demand levels—low (100 patients per annum), anticipated (200 patients per annum) and high (500 patients per annum)—to assess resource allocation, cost per treatment and system resilience to demand changes and to quantify the risks of mix-ups within the supply chain for the delivery of CAR T treatments.ResultsThe simulation results show that although centralized manufacturing offers better economies of scale, individual facilities in a decentralized system can spread facility costs across a greater number of treatments and better utilize resources at high demand levels (annual demand of 500 patients), allowing for an overall more comparable cost per treatment. In general, raw material and consumable costs have been shown to be one of the greatest cost drivers, and genetic modification-associated costs have been shown to account for over one third of raw material and consumable costs. Turnaround time per treatment for the decentralized scheme is shown to be consistently lower than its centralized counterpart, as there is no need for product freeze-thaw, packaging and transportation, although the time savings is shown to be insignificant in the UK case study because of its rather compact geographical setting with well-established transportation networks. In both schemes, sterility testing lies on the critical path for treatment delivery and is shown to be critical for treatment turnaround time reduction.ConclusionsConsidering both cost and treatment turnaround time, point-of-care manufacturing within the UK does not show great advantages over centralized manufacturing. However, further simulations using this model can be used to understand the feasibility of decentralized manufacturing in a larger geographical setting.     

Batch sizes and lead-time performance in flexible manufacturing systems

Production lead-time performance in flexible manufacturing systems is influenced by several factors which include: machine groupings, demand rates, machine processing rates, product batching, material handling system capacity, and so on. Hence, control of lead-time performance can be affected through the manipulation of one or more of these variables. In this article, we investigate the potential of batch sizing as a control variable for lead-time performance through the use of a queueing network model. We establish a functional relationship between the two variables, and incorporate the relationship in an optimization model to determine the optimal batch size(s) which minimizes the sum of annual work-in-process inventory and final inventory costs. The nonlinear batch sizing problem which results is solved by discrete optimization via marginal analysis. Results show that batch sizing can be a cheap and effective variable for controlling flexible manufacturing system throughput.     

Development of the anti-influenza H5N1 vaccines worldwide and in Russia

Article is dedicated to analytical investigation of the problem of current technologies in construction and manufacturing of anti-influenza vaccines. Epidemiological events in July-November 2005 in Russia (mainly in Siberia) and later in Ukraine showed that Health Care system was not ready for that turn over of epidemiological situation. It was completely the same situation in other countries. There are two general questions of a readiness in pre-pandemic situation: level of a diagnostic monitoring of epidemiological situation and preparedness to fast production of actual vaccine preparations. First task can be solved by immediate production of diagnostic sets for regional branches of National WHO Centers, and a second one depends on application of a novel approaches in construction of a anti-influenza vaccines. The construction of anti-influenza vaccines is based on genetic engineering (reverse genetics) and manipulation with plasmids carried out basic viral genes. Reassortation technology for preparation of hybrid viruses is going to the past by objective reasons. Advanced technologies are safety in laboratories and in manufacturing facilities. Moreover, genetic engineering in this field allows to planing the construction of vaccines bank, when the prognoses for actual viruses include more then two strains with different antigenic properties.     

Process and operations strategies to enable global access to antibody therapies

Few monoclonal antibodies are currently approved for treating infectious diseases, but multiple products are in development against a broad range of infectious diseases, including Ebola, influenza, hepatitis B, HIV, dengue, and COVID-19. The maturity of mAb technologies now allow us to identify and advance neutralizing mAb products to the clinic at “pandemic pace”, as the pipeline of mAbs targeting SARS-CoV-2 has demonstrated. Ensuring global access to these products for passive immunization, however, will require both low manufacturing cost and multi-ton production capacity—particularly for those infectious diseases where the geographic burden falls mostly in low- and middle-income countries or those with pandemic potential. Analysis of process economics and manufacturing technologies for antibody and other parenteral protein therapeutics demonstrates the importance of economies of scale to reducing the cost of goods for drug substance manufacturing. There are major benefits to convergence on a standardized platform process for antibody production that is portable to most existing very large-scale facilities, carries low risk for complications during process transfer and scale-up, and has a predictable timeline and probability of technical and regulatory success. In the case of an infectious disease with pandemic potential which could be treated with an antibody, such as COVID-19 or influenza, these advantages are paramount.     

An Evaluative Study of Operation Grouping Policies in an FMS

The increased use of flexible manufacturing systems to provide customers with diversified products efficiently has created a significant set of operational challenges for managers. This technology poses a number of decision problems that need to be solved by researchers and practitioners. In the literature, there have been a number of attempts to solve design and operational problems. Special attention has been given to machine loading problems, which involve the assignment of job operations and allocation of tools and resources to optimize specific measures of productivity. Most existing studies focus on modeling the problem and developing heuristics in order to optimize certain performance metrics rather than on understanding the problem and the interaction between the different factors in the system. The objective of this paper is to study the machine loading problem. More specifically, we compare operation aggregation and disaggregation policies in a random flexible manufacturing system (FMS) and analyze its interaction with other factors such as routing flexibility, sequencing flexibility, machine load, buffer capacity, and alternative processing-time ratio. For this purpose, a simulation study is conducted and the results are analyzed by statistical methods. The analysis of results highlights the important factors and their levels that could yield near-optimal system performance.     

Measuring efficiency and scope economies of cogeneration enterprises in Northeast China under the background of energy saving and emission reduction

Cogeneration is internationally recognized as an important way to save energy and improve environment. At present, the cogeneration scale in China has been ranked at the second place all round the world. China formulated relevant laws, regulations and technology policies to actively encourage and support the development of cogeneration. This article selects 62 Northeast regional Chinese cogeneration enterprises' financial data from 2003 to 2007, and analyzes the impact of the electric power industry deregulation to cogeneration enterprises' performance by using a partial frontier nonparametric. Further more, we study whether the cogeneration enterprises actualize horizontal scope economy by comparing with the thermal power alone or heat production alone enterprises. Results show that the factory network separation and regional market trial reform can promote the cost efficiency of both five major power group cogeneration enterprises and independent cogeneration enterprises. Compared to five group enterprises, the scope economies index of the independent cogeneration enterprises is lower, the unbundling reform and northeast regional market trial reform have a negative impact on cogeneration enterprises to achieve scope economies and improve cost efficiency.