Junfang Yu

A two-phase procedure for duplicating bottleneck machines in a linear layout, cellular manufacturing system

Abstract We discuss a two-phase procedure for duplicating bottleneck machines in a cellular manufacturing system. Given a preliminary solution by a clustering technique, the first phase solves a cellular layout problem in which it assigns machine-cells to locations to minimize the total inter-cell material handling costs that result from the bottleneck parts. The purpose of this phase is to find an optimal linear layout of cells. The second phase finds the bottleneck machines that need to be duplicated to minimize the costs. A binary (integer) linear programming model is developed in this phase to minimize the total duplication costs and material handling costs (if not duplicated). Finally, a decision is made as to whether a solution with bottleneck machines, or duplication of bottleneck machines to avoid the bottleneck problem is to be accepted. An example is demonstrated to show how such a bottleneck problem in cellular manufacturing is solved.

Single-Manufacturer, Multi-Retailer Consignment Policy for Retailers’ Generalized Demand Distributions

Consignment policy (CP) is a novel approach to the inventory management in supply chains. It is based on strong interaction and reliable collaboration between vendor(s) and buyer(s), which is acquiring growing importance in todays industrial reality. Unlike most literature focusing on single-vendor single-buyer models and deterministic customer demand, a single-manufacturer (vendor) multi-retailer (buyer) generic model is developed under stochastic customer demand in this study. In order to understand the potential benefits of CP, it is compared with a traditional policy (TP) model developed in the similar approach. The models are tested with two scenarios of uniform and exponential demand distributions of the retailers. The results show how CP works better than the traditional uncoordinated optimization. It not only helps the manufacturer to generate higher profit, but also coordinates retailers to achieve a higher supply chain profit. At the same time, each retailer earns at least as much as they do in TP. Further price discount sensitivity analysis demonstrates the efficiency of CP when facing price-demand fluctuation.

Directional decomposition heuristic for a linear machine-cell location problem

Abstract A machine-cell itself can be treated as a machine, and the location of such a cell in a linear line configuration reflects an analogy to the machine location problem. Thus, the problem addressed here is a one-dimensional equidistant machine-cell location problem that considers jobs with sequenced-operations, and the number of machine-cells equals the number of locations that are equally spaced in a linear layout. It is always desirable to achieve a cell assignment that minimizes the total inter-cell flows and, thus, the total inter-cell flow costs. This assignment problem can be formulated as a quadratic assignment problem the optimal solution to which is usually prohibitive since it is a non-deterministically polynomial hard problem, and a heuristic procedure is justifiably called for in this research. Many of the investigations involved in seeking an improved location assignment in heuristics are repeated from one search to another. Each branch of the search requires re-computation of all inter-cell flows, though only some of them have been changed from the previous one. Such a search mechanism requires considerable computation time, thus making the algorithm inefficient. This problem can be overcome by directionally decomposing the inter-cell flows and incrementally computing them. Based on the directional decomposition of these flows, a directional search is implemented in the heuristic in order to reduce the repetitiveness occurring in the traditional search. Both the partitioning procedure and the directional decomposition heuristic proposed here are demonstrated through examples, and the performance measures indicate the superiority of the heuristic over the existing methods.

Manufacturing lot-sizing, procurement and delivery schedules over a finite planning horizon

In this study, an integrated manufacturing system for technology-related companies whose products are experiencing continuous price decrease during the life cycle is studied for optimal procurement, production and delivery schedules over a finite planning horizon. The model considers the inventory cost both at manufacturing and at delivery from supplier. Since the price is continuously decreasing, a manufacturing firm delivers the finished goods in small quantities frequently. Frequent deliveries in small lots are effective to reduce the total cost of the supply chain. The key for high-tech industries is to reduce the inventory holding time since the component prices are continuously decreasing, and this can only be achieved by implementing an efficient supply chain. Therefore, the main purpose of this paper is to develop an integrated inventory model for high-tech industries in JIT environment under continuous price decrease over finite planning horizon while effectively and successfully accomplishing supply chain integration so that the total cost of the system is minimal. An efficient algorithm is developed to determine the optimal or near-optimal lot sizes for raw material procurement, and manufacturing batch under a finite planning horizon. Finally, the solution technique developed for the model is illustrated with numerical examples.

An integrated multi-stage supply chain inventory model under an infinite planning horizon and continuous price decrease

This paper studies an integrated inventory model in a supply chain that involves procurement, production and delivery activities. The model is studied in an environment where products experience continuous price decrease and planning is performed in an infinite time horizon. In this model, a manufacturing facility purchases a fixed-quantity of raw materials from an outside supplier, processes the materials, and delivers a fixed-quantity of finished products to a customer periodically. In order to take advantage of the decreasing price trend, customers demand frequent deliveries of small lots of finished products, and this inventory management strategy has been used by many successful companies in technology-related industries. Therefore, the ultimate intention of this research is to study and model the inventory system for high-tech companies whose products are experiencing continuous price decrease. This model is used to determine an optimal economic lot size model for raw material procurement, production setup and finished goods delivering under an infinite planning horizon. Two efficient algorithms are developed in this paper to solve this nonlinear model and the test results consistently indicate that ordering of raw materials and delivery of finished goods should be frequent in small lots for low ordering and shipment costs. Finally an operational schedule is provided to show the implementation procedure of the model.

Incorporating a Measure of Uncertainty into Systems of Systems Development Performance Measures

Technical Performance Measures TPMs historically are used to help the Program Manager in predicting if a program is on a path to achieve required performance. When extended over a developmental timeline, TPMs have provided a deterministic approach for predicting expected operational performance. However, TPMs are difficult to derive for a complex acknowledged system of systems SoS. An SoS Performance Measure SPM has been developed that is equivalent in purpose to TPMs and demonstrated for a deterministic state similar to TPM usage. However, reality indicates that many of the SoS component variables have significant uncertainty associated with them during the SoS development. Therefore, to more accurately account for the ability of an SoS to achieve its desired performance, this variability needs to be accounted for. This paper extends the deterministic SPM concept to a stochastic SPM to account for this uncertainty. An Antisubmarine Warfare ASW mission example is used, and demonstrates how this extension improves the effectiveness of the SPM methodology.

Systems requirements engineering—State of the methodology

There are many references about the characteristics of a good requirement. But what is the process for developing clear, unambiguous requirements, and how do we know when we have defined the requirements successfully? This paper investigates the current state of the methodology for developing complex system requirements. Significant work has been accomplished over the last several years to describe requirements development and systems engineering. This paper identifies and investigates requirements development methodologies and techniques. ©2012 Wiley Periodicals, Inc. Syst Eng 16

A balanced maintenance schedule for a failure‐prone system

Service systems that require failure rate below a predetermined value usually need maintenance in order to operate at that level of reliability. One major issue in maintenance systems is the optimal maintenance schedule that incurs minimum total cost. Considering fixed inflation rate and failure rate variation after maintenance, an algorithm of balanced maintenance scheduling is developed. The algorithm provides an optimal number of replacement and preventive maintenance to minimize the total maintenance cost over a certain planning period. A numerical example is demonstrated and compared with the results reported by other researchers.

A framework for performance prediction during development of systems of systems

This paper addresses the need for predicting performance in a system of systems (SoS) during development. Historically, technical performance measures (TPMs) along with modelling and simulation have been used by senior decision makers to predict if a system under development will meet the required performance needs. This methodology does not appear to be directly translatable to SoS’s for several reasons including the inherent complexity of the SoS and the operational flexibility the end user has in employing the SoS. An approach to dealing with the SoS performance prediction need is presented that addresses the use and integration of multiple technologies into a SoS and the decision maker’s options in the use of these technologies. This approach is used to develop a metric defined as a ‘SoS performance measure (SPM)’, an equivalent to a TPM for a SoS. An anti-submarine warfare mission construct is used to demonstrate this new metric.

A quadra-directional decomposition heuristic for a two-dimensional, non-equidistant machine-cell location problem

After the development of numerous cell formation techniques, machine-cell location (MCL) problems have been the focus of many researchers in cellular manufacturing systems. With the cost cutting strategy, locating machines within the cell itself has not only been the major concern of management, but also the location of cells with respect to each other on a spatial coordinate system to minimize the transportation cost or job movement costs. For lack of being able to solve a large problem optimally, a number of heuristics have been developed for one-dimensional machine and MCL problems. The problem still exists for locating machine-cells on spatial coordinates, which has been addressed in this research. The location coordinates have been decomposed into four movements, backward, forward, upward and downward; and the MCL problem is formulated as a linear combination of these four decomposed (partitioned) objective functions subject to other boundary conditions. A quadra-directional decomposition heuristic (QDDH) is developed to find a sub-optimal solution to the MCL problem. The decomposition procedure for four objective functions is presented and the performance of the heuristic is tested on a set of well-known data. Empirical tests show that the solution procedure produces efficient, good quality solutions for different sizes of the problem instances.