The measurement of flexibility in manufacturing systems

This article provides a theoretical basis for measuring the flexibility of manufacturing systems. The concept of multiple levels of measures (necessary, capability, actual, inflexibility, and optimality) for each flexibility type is introduced. Capability and actual measures are then developed for machine, routing, process, product, and volume flexibilities. For each of these flexibility types, a state defining variable is identified. A measure of flexibility is then derived by computing either, (i) the change effort expended in moving between states, (ii) the drop in system performance in moving between states, (iii) a general or physical scale of difference between two successive states, or (iv) a measure combining all three. The use of the developed measures is illustrated via a two-facility example.     

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.     

Inventory rationing for a system with heterogeneous customer classes

Many retailers find it useful to partition customers into multiple classes based on certain characteristics. We consider the case in which customers are primarily distinguished by whether they are willing to wait for backordered demand. A firm that faces demand from customers that are differentiated in this way may want to adopt an inventory management policy that takes advantage of this differentiation. We propose doing so by imposing a critical level (CL) policy: when inventory is at or below the critical level demand from those customers that are willing to wait is backordered, while demand from customers unwilling to wait will still be served as long as there is any inventory available. This policy reserves inventory for possible future demands from impatient customers by having other, patient, customers wait. We model a system that operates a continuous review replenishment policy, in which a base stock policy is used for replenishments. Demands as well as lead times are stochastic. We develop an exact and efficient procedure to determine the average infinite horizon performance of a given CL policy. Leveraging this procedure we develop an efficient algorithm to determine the optimal CL policy parameters. Then, in a numerical study we compare the cost of the optimal CL policy to the globally optimal state-dependent policy along with two alternative, more naïve, policies. The CL policy is slightly over 2 % from optimal, whereas the alternative policies are 7 and 27 % from optimal. We also study the sensitivity of our policy to the coefficient of variation of the lead time distribution, and find that the optimal CL policy is fairly insensitive, which is not the case for the globally optimal policy.     

Protein-protein docking with a reduced protein model accounting for side-chain flexibility

A protein-protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking minima on the protein surfaces within. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chemical character. Energy minimization of protein test complexes in the reduced representation results in geometries close to experiment with backbone root mean square deviations (RMSDs) of approximately 1 to 3 A for the mobile protein partner from the experimental geometry. For most test cases, the energy-minimized experimental structure scores among the top five energy minima in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound (apo) binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a solution within approximately 2 to 3.5 A RMSD of the full mobile partner from the experimental geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.     

Analysis of RNA flexibility by scanning force spectroscopy

Scanning force spectroscopy was used to measure the mechanical properties of double stranded RNA molecules in comparison with DNA. We find that, similar to the B–S transition in DNA, RNA molecules are stretched from the assumed A′ conformation to a stretched conformation by applying a defined force (plateau force). The force depends on the G + C content of the RNA and is distinct from that required for the B–S transition of a homologous DNA molecule. After the conformational change, DNA can be further extended by a factor of 0.7 ± 0.2 (S-factor) before melting occurs and the binding of the molecule to the cantilever is finally disrupted. For RNA, the S-factor was higher (1.0 ± 0.2) and more variable. Experiments to measure secondary structures in single stranded RNA yielded a large number of different force-distance curves, suggesting disruption and stretching of various secondary structures. Oriented attachment of the molecules to the substrate, a defined pick-up point and an increased resolution of the instrument could provide the means to analyse RNA secondary structures by scanning force spectroscopy.     

Source apportionment and health risk quantification for heavy metal sources in soils near aluminum-plastic manufacturing facilities in northeast China

Abstract

Identifying the source effect on heavy metals to human health risk is essential for devising and implementing restoration policies for polluted soils. For this purpose, eight heavy metals (As, Cd, Hg, Cr, Cu, Ni, Pb, and Zn) in soil profile samples (0–10, 10–20, 20–30, and 30–40?cm) collected in the area around aluminum-plastic manufacturing facilities (APMF) were determined. An absolute principal component score multiple linear regression (APCS-MLR) model supported by a health risk assessment (HRA) model was developed to determine the source apportionment of soil heavy metals and contribution rate of pollution sources to human health risk. Results showed significant accumulations of eight metals in the topsoil (0–20?cm), parent material, transportation, APMF, and agricultural practices were the four major contributing sources for heavy metals in soils, with average contribution percentages of 21.69%, 24.99%, 29.60%, and 14.25%, respectively. Carcinogenic risk factors for adults (1.23E-04) and children (1.32E-04) were found to be above the acceptable level (1E-06 to 1E-04). The health risk quantification results indicated that parent material, APMF, transportation, agricultural practices, and unidentified factors accounted for 55.76%, 14.48%, 12.09%, 10.13%, and 7.54% of the carcinogenic risk for children and adults. The adverse impacts of Cd, Zn, and Pb accumulations in soil coming from APMF activities were significant and need to receive more attention.     

A queueing model for a two-stage stochastic manufacturing system with overlapping operations

This paper presents analytical expressions for estimating average process batch flow times through a stochastic manufacturing system with overlapping operations. It is shown that the traditional queueing methodology cannot be directly applied to this setting, as the use of the overlapping operations principle causes the arrival process of sublots at the second stage to be a non-renewal process. An embedded queueing model is then proposed, which provides a tool to estimate the flow time reductions caused by the use of overlapping operations. Moreover, we provide expressions to estimate the production disruptions occurring at the second stage. The results of our research confirm the general intuition that the overlapping operations principle leads to less congestion, and hence a smoother flow of work through the system. On the other hand however, lot splitting inevitably requires more material handling on the shop floor. The expressions provided in this paper allow the quantification of the trade-off between these two effects, e.g., by gauging them within the scope of a cost model.     

Analysis of flexible manufacturing systems with distinct repeated visits: DrQ

This article examines the performance effects caused by repeated part visits at the workstations of a flexible manufacturing system (FMS). Such repeated part visits to the same workstations are commonly associated with fixture changes for machining complex parts, reclamping, and remounting or reorienting them. Since each of the repeated visits to a workstation may require different processing requirements, the resulting queueing network does not have a product form solution. We therefore develop an approximate mean value analysis model for performance evaluation of an FMS that may produce multiple part types with distinct repeated visits. We provide numerical examples and validate the accuracy of our solution algorithm against simulation. These examples show that the proposed model produces accurate throughput and utilization predictions with minimal computational efforts. These examples reveal that increasing the total pallet population may result in a reduction of the aggregate throughput, and that the FMS's performance could be more sensitive to the mix of pallets and part routes than to the total number of pallets. Our model will be of use, in particular, when managers wish to control individual operations (e.g., to adjust individual operation times to achieve economic savings in tool wear and breakage costs) or to investigate the performance implications of route changes due to alternate assignments of particular manufacturing tasks to certain workstations.     

GEOCHEM-EZ: a chemical speciation program with greater power and flexibility

GEOCHEM-EZ is a multi-functional chemical speciation program, designed to replace GEOCHEM-PC, which can only be used on DOS consoles. Chemical speciation programs, such as GEOCHEM and GEOCHEM-PC, have been excellent tools for scientists designing appropriate solutions for their experiments. GEOCHEM-PC is widely used in plant nutrition and soil and environmental chemistry research to perform equilibrium speciation computations, allowing the user to estimate solution ion activities and to consider simple complexes and solid phases. As helpful as GEOCHEM-PC has been to scientists, the consensus was that the program was not very user friendly, was difficult to learn and to troubleshoot, and suffered from several functional weaknesses. To enhance the usability and to address the problems found in GEOCHEM-PC, we upgraded the program with a Java graphical interface, added Help files, and improved its power and function, allowing it to run on any computer that supports Windows XP, Vista or Windows 7.     

Scheduling algorithms for a two-machine flexible manufacturing system

The flexible manufacturing system (FMS) considered in this paper is composed of two CNC machines working in series—a punching machine and a bending machine connected through rollers acting as a buffer system of finite capacity. The main difference between the present problem and the standard two-machine flow shop problem with finite intermediate capacity is precisely the buffer system, which in our problem consists of two stacks of parts supported by rollers: the first stack contains the output of the punching machine, while the second stack contains the input for the bending machine. When the second stack is empty, the first stack may be moved over. Furthermore, the capacity of each stack depends on the particular part type being processed. The FMS can manufacture a wide range of parts of different types. Processing times on the two machines are usually different so that an unbalance results in their total workload. Furthermore, whenever there is a change of the part type in production, the machines must be properly reset—that is, some tools need to be changed or repositioned. A second important difference between the present problem and the usual two-machine flow shop problem is the objective. Given a list ofp part types to be produced in known quantities, the problem considered here is how to sequence or alternate the production of the required part types so as to achieve various hierarchical targets: minimize the makespan (the total time needed to complete production) and, for instance, compress the idle periods of the machine with less workload into a few long enough intervals that could be utilized for maintenance or other reasons. Although Johnson's rule is optimal in some particular cases, the problem addressed in the paper isNP-hard in general: heuristic procedures are therefore provided.     

Dynamic load control policies for a flexible manufacturing system with stochastic processing rates

Real-time scheduling and load controls of FMSs are complex processes in which the control logic must consider a broad spectrum of instantaneous state variables while taking into account the probabilistic future impact of each decision at each time epoch. These processes are particularly important in the management of modern FMS environment, since they are known to have a significant impact on the FMS productive capacity and economic viability. In this article we outline the approach developed for dynamic load controls within an FMS producing a variety of glass lenses. Two revenue-influencing objective functions are evaluated for this capital-intensive facility. It is shown that by using Semi-Markovian modeling concepts, the FMS states need to be observed only at certain decision epochs. The mean holding time in each state is then obtained using the probability distribution function of the conditional state occupancy times. Several key performance measures are then derived by means of the value equations. In addition, the structure of the optimal policies are exemplified for a variety of operational parameters. It is shown that the optimal policies tend to generate higher buffer stocks of parts in those work centers having the highest revenue-generation rates. These buffer stocks get smaller and smaller as the relative processing capacity of the centers increases. Similar observations lead us to the introduction of several promising heuristics that capture the structural properties of the optimal policies with a significantly smaller computational effort. Results of the empirical evaluation of these heuristics are also analyzed here.