Aligning manufacturing flexibility with environmental uncertainty: Evidence from high-technology component manufacturers in Taiwan

While flexibility improvement is among the top concerns of manufacturing managers, managers are advised to choose the dimensions of flexibility they want in their plants. This study investigates the strategic choice of aligning flexibility development with the external environment that manufacturing managers face. Considering the nature of the high-technology industry in Taiwan, we measure environmental uncertainty based on the dimensions of customer demand, supply, competitors and product technology. Empirical data were collected from manufacturing firms in Taiwan. We then applied path analysis to examine the effect of aligning three types of flexibility: product mix, new product and volume with specific dimensions of environmental uncertainty. The results indicate that the matching of manufacturing flexibility with environmental uncertainty is necessary to ensure profit and sales performance. When faced with certain environmental stimuli, management should choose to emphasize and develop particular manufacturing flexibility.     

Pricing and ordering strategies in manufacturing and distribution alliances

This paper studies the effect of coordination in a manufacturing and distribution system consisting of one manufacturer and one distributor. The system operates to meet price-sensitive random demand with the objective of maximizing expected profits of both the manufacturer and the distributor. The coordinated pricing and production/ordering policies that maximize the expected profits of the manufacturer and the distributor, as well as the distributor's optimal pricing and ordering policies without coordination, are developed. The focus of this study is to address the following managerial questions: What factors make coordination an effective strategy for both the manufacturer and the distributor? What are the coordination strategies and the coordinated policies that maximize both parties' expected profits and the joint expected profit? These and other related managerial issues are explored in this paper.     

Taxonomy of the manufacturing strategies of large Spanish industrial companies

This work presents a classification of the manufacturing strategies of large Spanish industrial companies in Spain. For this purpose the various international empirical studies on alternative manufacturing strategies have been taken as a reference, reviewed and compared. The database used in this study is made up of information on 114 factories and has been designed using the information from a survey mailed to the industrial companies which have production plants in Spain and which in the financial year of 1994 (reference date of this research) employed over 200 workers. Cluster analysis methodology has been used and the classification criterion taken was the competitive advantages or strengths of each factory concerning the five competitive priorities in manufacturing: efficiency, flexibility, quality, delivery and customer service. Finally, this work identifies a taxonomy of the manufacturing strategies of a sample of the largest industrial companies in Spain, differentiating three alternative production strategies: flexible marketoriented manufacturers, low-cost quality manufacturers and delivery-based manufacturers. Large industrial companies analysed compete in manufacturing, basically following a choice of three criteria: flexibility, quality or delivery. The companies belonging to each of the three categories identified maintain common and lasting manufacturing objectives and policies.     

Additive manufacturing: scientific and technological challenges,market uptake and opportunities

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Alternative production strategies based on the comparison of additive and traditional manufacturing technologies

Additive manufacturing technology has been evolving for several years. New material options, better processing speeds and greater autonomy are some of the characteristics of this technology that are still under research. However, in its current state, many commercially available 3D printers are competing with traditional manufacturing techniques in the fabrication of end-use products. In this paper, different additive manufacturing technologies are compared with injection moulding in a real-world case study. The comparison is conducted in terms of lead time and total production cost. From the case under study, it becomes obvious that none of the additive manufacturing technologies examined is yet able to practically replace injection moulding for medium- and high production volumes. However, when considering low-volume production, both rapid tooling and additive manufacturing may offer an alternative that could result into shorter lead times and decreased total production costs. In addition, the introduction of Additive Manufacturing in a producer’s production portfolio can increase flexibility, reduce warehousing costs and assist the company towards the adoption of a mass customisation business strategy.     

Launching and dispatching strategies for multi-criteria control of closed manufacturing systems with flexible routeing capability

In this paper, we study the problems of launching and dispatching of parts in closed manufacturing systems with flexible routeing. For the manufacturing systems being operated against multiple performance criteria, we postulate that controlling different aspects of the operational control strategy to meet one single performance criterion would improve overall system performance. It is suggested that to achieve production rates, launching rules be utilized and to affect flowtime, dispatching rules be manipulated. Also, for measurement of routeing flexibility, an entropic measure of flexibility is refined. The entropy-based rule is then compared with the dispatching rules commonly used in the industry. Control strategies are developed for a test system and it is shown that a hierarchical control strategy works best when multiple performance criteria are of interest.     

Product complexity and design of inspection strategies for assembly manufacturing processes

In the manufacturing field, the assembly process heavily affects product final quality and cost. Specific studies, concerning the causes of the assembly defects, showed that operator errors account for high percentage of the total defects. Also, models linking the assembly complexity with the operator-induced defect rate were developed. Basing on these models, the present paper proposes a new paradigm for designing inspection strategies in case of short-run productions, for which traditional approaches may not be carried out. Specifically, defect generation models are developed to get a priori predictions of the probability of occurrence of defects, which are useful for designing effective inspection procedures. The proposed methodology is applied to a case study concerning the assembly of mechanical components in the manufacturing of hardness testing machines.     

Development of manufacturing control strategies using unsupervised machine learning

This research considers the control of manufacturing systems that support job routing and process sequence flexibility. A machine learning system is presented that uses a simulation model of the target manufacturing system to discover opportunistic control rules. Learning is unsupervised and is driven by a genetic algorithm. The learning method requires very little a priori control knowledge. For this presentation, the decision-making agents are the part types being processed. Part types evolve cooperative strategies for selecting the best route through the manufacturing system based on simulated real-time information that describes the state of the system. Results are presented that demonstrate the effectiveness of the approach.     

Optimal core acquisition and pricing strategies for hybrid manufacturing and remanufacturing systems

In this study, we combine two aspects of remanufacturing, namely product acquisition management and marketing (pricing) of the remanufactured products. We consider an original equipment manufacturer (OEM) who decides on the acquisition prices offered for returns from different quality types and on selling prices of new and remanufactured products, in a single period setting. We develop a procedure for determining the optimal prices and corresponding profit of the OEM, and conduct a sensitivity analysis to understand the effect of different model parameters on the optimal strategies and profit. An important managerial insight is that the optimal solution is not to have the same profit per remanufactured item for all return types, but to if the minimum cost for acquisition and remanufacturing of some core type is lower.     

A longitudinal study of the impact of market requirements focus on manufacturing performance

This paper examines the longitudinal relationship between market requirements focus and manufacturing performance in a sample of automotive supplier plants. Statistical analysis indicates that, overall, an increase in market requirements focus from 1995 to 1999 was associated with an increase in manufacturing performance over the same time period, while a decrease in focus was associated with decreasing performance. Furthermore, plant manager interviews suggest that plant-level involvement and firm resource commitment may serve to leverage focus improvement efforts, or moderate the negative effects of decreasing focus.     

Pricing strategies for information products with network effects and complementary services in a duopolistic market

In this paper, we model a fully covered duopoly market in which two firms offer a differentiated information product that exhibits positive network effects and a complementary premium service to consumers. For each firm, there are two marketing strategies: the freemium strategy and the bundling strategy. We find that, under the market equilibrium, a firms’ decision whether to employ the freemium strategy or not depends largely on the quality of the information product compared to its rival. When the information product quality is similar and the products’ intrinsic values are sufficiently large, both firms will be better off by adopting the freemium strategy, while the bundling strategy will prevail if the products’ intrinsic values are sufficiently small. Additionally, when the magnitude of complementary effects or network effects exceeds a given threshold, both firms’ profit can be enhanced by an increase in the degree of product complementarity or in the intensity of network effects. We also demonstrate that a firm can benefit from an increasing market size only if the intrinsic value of its information product is sufficiently large. Finally, we extend our model to the uncovered market and derive the equilibrium prices and profits.     

Capacity-based order review/release strategies to improve manufacturing performance

Given the increased emphasis by manufacturing organizations to reduce work-in-progress inventories thereby shortening their manufacturing lead times, more attention is being given to the control of the materials released to the shop floor. The control of input into the shop is one of the activities associated with order review/release (ORR). A common assumption of the published literature on ORR is that all orders received by the shop will be accepted, regardless of shop conditions. In this paper, this assumption is relaxed such that in times of high shop congestion, it may be better to reject an order to allow the customer to seek another supplier than to accept the order and deliver it to the customer late. When the shop is highly congested, accepting all orders will jeopardize the ability of the shop to meet customer due dates. In an industry that demands fast and reliable turnaround of customer orders, not meeting due dates may result in customers placing their orders with other more reliable suppliers. Of course, rejecting the order outright will also have some negative effects. The best alternative would depend on the preferences by managers and the tradeoffs involved between rejecting the order or accepting the order and then not meeting the customer due date. Three methods to determine whether or not to accept the order were tested in this research. Results suggest the consideration of shop loads is better than a random rejection in determining whether an order should be accepted or rejected by the shop. Also, an analysis of the load on the orders routeing is more effective than considering the overall load in the shop.     

Assessing intermediate infrastructural manufacturing decisions that affect a firm's market performance

The purpose of this study is to develop a strategic operations management model that links intermediate infrastructural operations decisions and market performance given process choice as a structural constraint for manufacturing firms. The results underscore the effects of manufacturing control and staff skill and knowledge development on a firm's market performance. Several conclusions are drawn. First, manufacturing control, and staff skill and knowledge development has played significant roles in determining market performance. Second, either alone or in tandem with other independent variables, technology application dose not appear to be the most critical factor to affect a firm's market performance in today's Chinese business environment. Third, process type may not have a direct impact on market performance.     

Manufacturing strategies for the ecosystem-based manufacturing system in the context of 3D printing

This paper aims to investigate the manufacturing strategies for the manufacturing systems in the context of 3D printing, referring to ecosystem-based manufacturing systems, rather than firm-based and network-based ones. A case study approach was adopted for this research, as the data was mainly collected via semi-structured interviews with staff members of companies in China. Besides the elements of strategic choices and manufacturing capabilities identified in the extant literature, this research verified three additional strategic choice elements (functional role, platform and solution) and identified two factors (platform openness and solution diversity) to classify an ecosystem-based manufacturing system. Meanwhile, four manufacturing capabilities of the ecosystem-based manufacturing system have been identified: collaborative manufacturing flexibility, rapid thriftiness ability, self-customisation and co-evolved design capability. The research results contribute to the area of manufacturing strategy via expanding its view from the firm and network levels to the ecosystem level. Meanwhile, the research results present operations managers with an understanding of the strategic choices and manufacturing capabilities of an ecosystem-based manufacturing system in the context of 3D printing.     

A comparative study of the operations strategies of globally- and domestically-oriented New Zealand manufacturing firms

There has been much written on why and how firms become involved in entering international markets. There is less material on the production/operations actions taken by such firms. This paper investigates the differences in competitive capabilities and manufacturing performance improvement plans between globally-oriented and domestically-oriented firms. It uses data collected from 140 New Zealand manufacturing companies. The results indicate that both groups emphasize the same competitive capabilities, but the globally-oriented group is placing more emphasis on some action plans involving quality assurance, improving existing processes and design for manufacture. Their most favoured action plans are similar to those of firms in most advanced manufacturing countries which participate in the Manufacturing Futures Project.     

Comparing the impact of different rescheduling strategies on the entropic-related complexity of manufacturing systems

The primary objective of this paper is to compare five rescheduling strategies according to their effectiveness in reducing entropic-related complexity arising from machine breakdowns in manufacturing systems. Entropic-related complexity is the expected amount of information required to describe the state of the system. Previous case studies carried out by the authors have guided computer simulations, which were carried out in Arena 5.0 in combination with MS Excel. Simulation performance is measured by: (1) entropic-related complexity measures, which quantify: (a) the complexity associated with the information content of schedules, and (b) the complexity associated with the variations between schedules; and (2) mean flow time. The results highlight two main points: (a) the importance of reducing unbalanced machine workloads by using the least utilised machine to process the jobs affected by machine breakdowns, and (b) low disruption strategies are effective at reducing entropic-related complexity; this means that applying rescheduling strategies in order to manage complexity can be beneficial up to a point, which, in low disruption strategies, is included in their threshold conditions. The contribution of this paper is two-fold. First, it extends the application of entropic-related complexity to every schedule generated through rescheduling, whereas previous work only applied it to the original schedule. Second, recommendations are proposed to schedulers for improving their rescheduling practice in the face of machine breakdowns. Those recommendations vary according to the manufacturing organisations’ product type and scheduling objectives. Further work includes: (a) preparing a detailed workbook to measure entropic-related complexity at shop-floor level; and (b) extending the analysis to other types of disturbances, such as customer changes.     

Effect of manufacturing system constructs on pick-up and drop-off strategies of multiple-load AGVs

This research investigates the interaction between manufacturing system constructs and the operation strategies in a multiple-load Automated Guided Vehicle System (AGVS) when AGVs in a system can carry two or more loads. The load pick-up problem arises when an AGV stops at a pick-up queue and has to decide which part(s) in the queue should be picked up. Since an AGV can carry multiple loads, a drop-off rule is then needed to determine the next stop for the AGV to deliver one or more loads. Several real-time composite heuristic rules for selecting load and determining the next stop are proposed and evaluated in two manufacturing system constructs: the jobshop and the flexible manufacturing system (FMS). A number of simulation models are developed to obtain statistics on various performance measures of the two system constructs under different experimental conditions. The simulation results reveal that the pick-up rules affect the system more than the drop-off rules. In general, rules to avoid starving and blocking in workstations perform better than the rules for shortest distance in throughput. However, the rules perform differently in jobshop and FMS based on other performance measures, indicating an interaction between system constructs and load selection strategies. The difference in rule performance within the same construct is also affected by several AGVS design parameters. Overall our study suggests that no load pick-up rule is always a champion, and the design of an efficient multiple-load AGVS must consider all issues in a global fashion.     

A framework to engineer production control strategies and its application in electronics manufacturing

One of the most challenging tasks of companies with complex and discrete production systems is to determine an appropriate production control strategy (PCS). The PCS is crucial, as it influences inventory, costs, and service. We propose a framework to address the most important questions of PCS engineering: limiting work in process, positioning the order penetration point (OPP), and coping with demand uncertainty upstream the OPP. Thereby, uncertain advance demand information in the form of forecasts is considered and desirable characteristics of push and pull strategies are combined. A serial manufacturing system with multiple products, variable processing times, and uncertain advance demand information is examined. The model is formulated as a queuing network model and solved numerically by discrete-event simulation. The framework and a resulting hybrid control strategy are applied to a case study from electronics manufacturing, where a significant improvement potential is identified.