Mitigating the bullwhip effect by reducing demand variance in the supply chain

To coordinate an agile manufacturing system with the high-level requirements of marketing services, supply chain management (SCM) plays an important role in management activities for enterprise globalization. In SCM, a phenomenon called the “bullwhip effect” has attracted considerable attention. Beyond the previous studies, we consider multiple retailers with one supplier in the supply chain and examine ways in which the supplier can reduce the total demand variance by adjusting retailers’ order sizes. The results reveal that the total demand variance can be reduced by using portfolio theory to adjust the order sizes based on the variance of order of the retailer. Therefore, the bullwhip effect can be partially reduced by our proposed method .     

Implementation of a “backwards planning” technique in the automation of process planning

It is essential to automate the process-planning function to achieve true integration of CAD and NC machining for computer-integrated manufacturing. Several planning techniques have been used for this purpose and the popular method called the “bottom-up” approach or “backwards planning” has been successfully used in developing an expert process-planning system called EXCAP. This paper describes the implementation of this approach, providing details and examples of the model-updating module which enables the planning to be executed automatically for turned components.     

Dynamic modeling and cooperative control of a redundant manipulator based on decomposition

This paper demonstrates the use of a redundant manipulator to execute multiple tasks specified at different points on the manipulator. This is accomplished by decomposing a redundant arm at an intermediate arm location, called “elbow”, into two non-redundant local arms, referred to as the “bascarm” and the forearm. This decomposition transforms a redundant arm into a “serially linked dual-arm system,” where the cooperation between the basearm and the forearm is carried out through the task distribution and the elbow control. To distribute a given task to individual local arms according to their dynamic capabilities, the Cartesian space model of a serially linked dual-arm system is derived using Lagrangian mechanics. The Cartesian space dynamic model enables us to quantify the dynamic capbilities of individual arms based on two hyper ellipsoids: the Cartesian Force Ellipsoid (C. F. E.) representing the range of Cartesian forces due to the unit norm of joint torques, and Cartesian Acceleration Ellipsoid (C. A. E.) representing the range of Cartesian accelerations due to the unit norm of Cartesian forces. In addition to the local dynamic characteristics, the global task requirements such as singularity avoidance, joint torque limit avoidance, motion generation efficiency, and accurate motion control, are improved by elbow control. Elbow control can also be used to execute a subtask at the elbow, for example, obstacle avoidance.     

Design and static performance of high speed machining centre with “direct drive”

“Direct drive” is an ideal method for speeding machine tools. In the structure of a CNC machining centre with “direct drive”, the linear motor’s primary and secondary parts are assembled into the worktable and machine bed respectively to directly drive the worktable. The built-in rotary motor is assembled in the spindle to realize the main transmission system of the machine tool “direct drive”. All mechanical transmission elements in machine tools are eliminated. High speed, efficiency, and accuracy are easily obtained. However, in this type of “direct drive” machining centre, the magnetic attraction force between the primary and the secondary linear motors and the dynamic impact at acceleration and deceleration are directly imposed on the machine tool, and influence the performance of the machining centre. This paper analyzes the special demands of “direct drive” on the machine centre, and introduces a new structure of the machining tool. The worktable and machine bed are optimized to meet the special demands of “direct drive”. Static performance simulation on the machining centre is done to reveal an ideal result.     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or sub-systems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or subsystems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

Supply chain management program first- and second-order effects model: a new strategic tool

Utilisation of supply chain management (SCM) strategies have an implicit objective of gaining an advantage over one’s business arena partners, whether they be competition or supply chain partners; an SCM-derived competitive advantage. A literature review accentuated four bases of strategic competition (cost-based, resource-based, time-based and knowledge-based), upon which, such an SCM-derived competitive advantage might be built. A Monash University qualitative research study found that the majority of small- to medium-sized firms have found this to be a risky and unprofitable endeavour. In response, this paper explores the four bases of strategic competition through an exemplary success case found within the Australian textiles, clothing and footwear (TCF) industry. The research raised a proposition stated as “effective supply chain management increases shareholder value (SHV).” An effective SCM program influences key success drivers (e.g. expenses, asset utilisation and process cycle time) available to it in a manner that maximises the firm’s competitive position, given its chosen strategy. This paper presents a first- to second-order SCM effects matrix model as a small step towards the mainstream achievement of current world-wide best SCM practice. The matrix can be utilised by individuals planning supply chain change processes or teams evaluating potential change initiatives within their supply chain operations. The substructure of the matrix is examination by isolating just the time-based strategic key success drivers, as found in the literature. The matrix’s utilisation methodology is detailed to enable its application by practitioners.     

Online qualitative nugget classification by using a linear vector quantization neural network for resistance spot welding

Real-time estimation of weld quality from process data is one of the key objectives in current weld control systems for resistance spot-welding processes. This task can be alleviated if the weld controller is equipped with a voltage sensor in the secondary circuit. Replacing the goal of quantifying the weld quality in terms of button size by the more modest objective of indirect estimation of the class of the weld, e.g., satisfactory (acceptable, “normal” button size), unsatisfactory (undersized, “cold” welds), and defects (“expulsion”), further improves the feasibility of the mission of indirect estimation of the weld quality. This paper proposes an algorithmic framework based on a linear vector quantization (LVQ) neural network for estimation of the button size class based on a small number of dynamic resistance patterns for cold, normal, and expulsion welds that are collected during the stabilization process. Nugget quality classification by using an LVQ network was tested on two types of controllers; medium-frequency direct current (MFDC) with constant current controller and alternating current (AC) with constant heat controller. In order to reduce the dimensionality of the input data vector, different sets of features are extracted from the dynamic resistance profile and are compared by using power of the test criteria. The results from all of these investigations are very promising and are reported here in detail.     

Production monitoring—A proven productivity tool

Production executives in modern factories are concerned with standards, real production and schedule maintenance, and with having early foresight into problem areas. The use of digital computers in the factory has for many years been largely divided between “closed-loop control” and “data processing” (DP), but today there is a growing need for “closed-loop information control” (CLIC). This paper describes a system for implementation of this concept using exclusively industry-standard hardware, and its application within smaller industrial operations rather than the industrial giants (although their need may indeed be greater). For many such smaller companies, production monitoring may be a first venture into CIM. Rather than “control” or “data” being the key, “information” is the cornerstone of the system described. The word “information” conjures up a variety of ideas in its normal use, but a visit to a real factory forces a closer look at its meaning, if the CLIC concept is to be even worth considering. Repeatable and verifiable data sources are very difficult to obtain on the factory floor. Physical compatibility is a real concern, because equipment that operates in the usual controlled DP environment is not usually reliable on the factory floor. The operating conditions demanded by much to today's DP equipment preclude heat, vibration, electromagnetic interference and the generally hostile conditions which are prevalent in many factories. Consequently, any factory-floor system is fraught with unique problems all the way from data capture, through communications, into efficient data structures and meaningful graphic presentation. This paper describes such a system and summarises its effect on productivity as proven by application in several factories in the US and Canada.     

Anomalous Low Friction Under Boundary Lubrication of Steel Surfaces by Polyols

We present here anomalous low friction obtained with highly polished steel on steel hard contact lubricated by glycerol under severe mixed and boundary regimes (λ ratio below 1). We investigated the effects of contact pressure, sliding speed, and temperature on friction coefficient and electrical contact resistance. The mechanism of low friction (typically below 0.02) is thought to have two origins: first a contribution of an ultrathin EHL film of glycerol providing easy shear under pressure, second the chemical degradation of glycerol inside the contact when more severe conditions are attained, generating a nanometer-thick film containing shear-induced water molecules. This new mechanism, called “H-bond Network model”, is completely different from the well-accepted “Monolayer” model working with polar molecules containing long aliphatic chains. Moreover, we show outstanding superlubricity (friction coefficient below 0.01) of steel surfaces directly lubricated by a solution of myo-inositol (also called vitamin Bh) in glycerol at ambient temperature (25 °C) and high contact pressure (0.8 GPa) in the absence of any long chain polar molecules. Mechanism is still unknown but could be associated with friction-induced dissociation of inositol and H-bond interactions network of water-like species with steel surface.     

Mass Customization: Metrics and Modularity

Mass customization as a competitive strategy is getting progressively increasing attention in business and academic arenas due to its high potential to provide sustained strategic advantage in a unique fashion. It is well documented that a manufacturing company competes with others in its industry on five dimensions: Price, quality, flexibility, delivery, and service. According to the existing literature, mass customization provides significant strategic advantage in two of these dimensions—price and customization. We, however, argue that when properly implemented, the cellular manufacturing structure associated with the appropriate implementation of mass customization strategy, provides additional competitive value in quality and delivery. Furthermore by virtue of the customer co-design as an integral aspect of mass customization, customer satisfaction also improves under this strategy. Mass customization strategy, therefore, provides competitive advantage in all five competitive dimensions simultaneously—a truly unique strategic accomplishment. We also propose, in this paper, new metrics for mass customization strategy that measure the “mass” as well as the “customization” aspects of this strategy. Finally, we describe in the clearest terms the modus operandi of modularity in product design and the role it plays in bringing about high levels of customization on one hand and economies of scale at component level, on the other. We conclude with remarks that underscore the need for conducting research in the areas at the interface of mass customization and supply chain management.     

A Further Discussion on Trends in the Development of Advanced Manufacturing Technology

This paper is a supplement to “Trends in the Development of Advanced Manufacturing Technology” (Yang and Wu in Chin. J. Mech. Eng., 39: 73, 2003) but delves deeper into it. It first points out the strategic status of manufacturing industry in state development. Then, a detailed analysis is given on the features and trends in the development of advanced manufacturing technology in a total of 12 points from three aspects: “precision,” “extreme,” and “culture” from the aspect of the product itself; “green,” “rapidness,” “saving,” and “efficiency” during the manufacturing process; and “digit,” “auto,” “integration,” “networking,” and “intelligence” in view of the manufacturing method. In addition, it emphasizes that all the above aspects should be based on two base points: “manufacture” and “machinery.” Finally, it puts forth the guiding ideologies for the development of advanced manufacturing technology and the aspects China should give priority to in development, while stressing on the principles of independence, innovation and “human orientation.”     

Parameter optimization of non-vertical laser cutting

In some cases, in order to avoid interference during 3D laser cutting of thin metal a laser head could not be kept vertical to the surface of a work piece. In such situations, the cutting quality depends not only on “typical” cutting parameters but also on the slant angle of the laser head. Traditionally, many tests had to be done in order to obtain the best cutting results. In this paper, an experimental design is employed to reduce the number of tests and an artificial neural network (ANN) is set up to describe quantitatively the relationship between cutting quality and cutting parameters in the non-vertical laser cutting situation. A quality point system is used to evaluate the cutting result of the thin sheet quantitatively. Testing of this novel method shows that the calculated “quality point” using ANN is quite closely in accord with the actual cutting result. The ANN is very successful for optimizing parameters, predicting cutting results and deducing new cutting information.     

Modelling knowledge related to the allocation of modular jigs for part fixturing using fuzzy reasoning

One the problems a workholder designer faces in attempting to gain knowledge about the modelling of the “wear” in a positioning system by means of allocating positioning devices to each “virtual”locating point is that this knowledge is often verbalized by experts in an imprecise and uncertain way. Knowledge comes from technological know-how, and is developed through experience, personal habits and production-specific requirements. Nevertheless, current modelling of “expert knowledge” does not allow us to represent the different semantics (such as imprecision and uncertainty) that are related to it. In this paper, we present a method based on fuzzy reasoning that is able to support the modelling of these different knowledge semantics .     

Proposal of new eco-manufacturing feature interaction-based methodology in CAD phase

Following the environmental crises of recent decades, a turning point in the awareness of the fragility of ecosystems has been marked, i.e., environmental awareness. This has contributed to the development of various environmental laws and regulations such as the “Waste Electrical and Electronic Equipment,” the “Restriction of Hazardous Substances,” and the “Registration, Evaluation, Authorization and Restriction of Chemicals” regulations and the “Energy Using Products” Directives. Our work contributes to the development of eco-friendly product manufacturing processes. In order to estimate and optimize the environmental impacts of a product, most of the methodologies, concepts, and tools that integrate computer-aided design (CAD) and life cycle assessment systems generally exploit the feature technology at the level of each feature independently of the others, i.e., “microplanning.” The feature interaction technology (FIT) is treated only in few studies, but it is pivotal in the eco-manufacturing process. In this paper, we propose a new manufacturing-scenarios-based methodology by using FIT and a Multi-criteria Decision Support Method (MCDSM), which helps manufacturers maintain their marketplaces by producing goods in an eco-friendly way. In fact, this methodology helps designers choose from the CAD design phase the most ecological manufacturing process from possible existent scenarios in real time.     

A mutual beneficial pricing strategy of an integrated vendor-buyers inventory system

This study develops an optimal pricing and replenishment policies in a “leagile” (lean and agile) supply chain system for a single vendor and multiple buyers. Since it benefits the vendor more than the buyers in the integrated system, a pricing strategy with price reduction is incorporated to entice the buyers to accept the minimum total cost integrated system. Negotiation factors are incorporated to balance the cost saving between the players. A numerical example with sensitivity analysis is provided to demonstrate the theory and the cost savings when integration is considered. The price reduction mechanism is a mutual beneficial strategic partnership between the vendor and the buyers.     

Analysis of the HVAC system’s sound quality using the design of experiments

Human hearing is very sensitive to sound, so a subjective index of sound quality is required. Each situation of sound evaluation is composed of Sound Quality (SQ) metrics. When substituting the level of one frequency band, we could not see the tendency of substitution at the whole frequency band during SQ evaluation. In this study, the Design of Experiments (DOE) is used to analyze noise from an automotive Heating, Ventilating, and Air Conditioning (HVAC) system. The frequency domain is divided into 12 equal parts, and each level of the domain is given an increase or decrease due to the change in frequency band based on the “loud” and “sharp” sound of the SQ analyzed. By using DOE, the number of tests is effectively reduced by the number of experiments, and the main result is a solution at each band. SQ in terms of the “loud” and “sharp” sound at each band, the change in band (increase or decrease in sound pressure) or no change in band will have the most effect on the identifiable characteristics of SQ. This will enable us to select the objective frequency band. Through the results obtained, the physical level changes in arbitrary frequency domain sensitivity can be determined.     

Road profile estimation using neural network algorithm

This paper more specifically focuses on the estimation of a road profile (i.e., along the “wheel track”). Road profile measurements have been performed to evaluate the ride quality of a newly constructed pavement, to monitor the condition of road networks in road management systems, as an input to vehicle dynamic systems, etc. The measurement may be conducted by a slow-moving apparatus directly measuring the elevation of the road or using a means that measures surface roughness at highway speeds by means of accelerometers coupled with high speed distance sensors, such as laser sensors or using a vehicle equipped with a response-type road roughness measuring system that indirectly indicate the user’s feelings of the ride quality. This paper proposes a solution to the road profile estimation using an artificial neural network (ANN) approach. The method incorporates an ANN which is trained using the data obtained from a validated vehicle model in the ADAMS software to approximate road profiles via the accelerations picked up from the vehicle. The study investigates the estimation capability of neural networks through comparison between some estimated and real road profiles in the form of actual road roughness and power spectral density.     

Effect of boundary layer swirl on supersonic jet instabilities and thrust

This paper reports the effects of nozzle exit boundary layer swirl on the instability modes of underexpanded supersonic jets emerging from plane rectangular nozzles. The effects of boundary layer swirl at the nozzle exit on thrust and mixing of supersonic rectangular jets are also considered. The previous study was performed with a 30° boundary layer swirl (S=0.41) in a plane rectangular nozzle exit. At this study, a 45° boundary layer swirl (S=1.0) is applied in a plane rectangular nozzle exit. A three-dimensional unsteady compressible Reynolds-Averaged Navier-Stokes code with Baldwin-Lomax and Chien’sk-ε two-equation turbulence models was used for numerical simulation. A shock adaptive grid system was applied to enhance shock resolution. The nozzle aspect ratio used in this study was 5.0, and the fully-expanded jet Mach number was 1.526. The “flapping” and “pumping” oscillations were observed in the jet’s small dimension at frequencies of about 3,900Hz and 7,800Hz, respectively. In the jefs large dimension, “spanwise” oscillations at the same frequency as the small dimension’s “flapping“ oscillations were captured. As reported before with a 30° nozzle exit boundary layer swirl, the induction of 45° swirl to the nozzle exit boundary layer also strongly enhances jet mixing with the reduction of thrust by 10%.