Machine repairing models for production systems

In this paper we consider manufacturing systems of m identical unreliable machines producing one type of product. The operating time of each machine is exponentially distributed. The repairing process of a machine requires more than one phase. In each phase, the repair time is exponentially distributed and more than one operator may be required for fixing a broken machine. Here we consider two models of manufacturing systems. In the first model, there are r operators assigned in one server to repair a broken machine. The repairing rate in each phase depends on the number of operators there. This is a generalized model discussed in Buzacott and Shanthikumar [11]. We then consider a two-phase repairing model. Two groups of operators are assigned in the two phases. Each operator can handle one broken machine in each phase individually. This model is a generalization of Eben–Chaime's model [8]. Average profits are derived for both models and can be optimized by suitable allocation of the number of machines and operators in the systems.     

Approximation approach for the performance analysis of production lines under a kanban discipline

In a JIT production environment, pull-type control systems are usually implemented to reduce the lead time and to synchronize the production rate with the demand rate. The design of an effective production control system requires easy and reliable approaches for evaluating the effect of the major system parameters on its performance.In this paper we model the kanban control system of a manufacturing line as a Markov process. In addition, we develop an approximation approach to the model that permits reliable evaluation of manufacturing system performance in terms of throughput time and work-in-process. The validation of the approach is implemented by comparing the exact results (based on discrete event simulation) and the approximated results.A good approximation is observed for a large range of conditions.     

The dynamics of just-in-time

This article analyses the impact of just-in-time production on the three resources of machines, materials and people, and suggests that JIT entails a redistribution of slack between these resources. The impact of JIT on an organization's human resources is particularly problematical; pressures towards both increased variety and intensity of work are apparent.     

Reengineering the production planning process in the food industry

This paper addresses managerial process reengineering and in particular the reengineering of the production planning process. The reengineered process highlights planning options to avoid the process imbalance and loss of production potential that can follow innovation in a facility that is fully committed to JIT production.The study was motivated by production problems following product innovation within the food industry but the reengineering conclusions and procedures are applicable to all similarly structured industries. An example based on data from a snack food manufacturing company illustrates the reengineered procedure for a plant that is typical of the food processing industry.     

The economic dynamics of work

Only by developing management systems based on appropriate standards can a business successfully learn how to improve the technology of work. As a result, a new economics of work is created where the evolution of large organizations makes economic sense. But economies of scale no longer require rigid mass production of a limited product line. Flexibility can be introduced to produce product diversity without losing the efficiencies of standardization. Thus manufacturing can operate more flexibly like a service by learning to apply industrial robots and other smart machines. Service businesses can also learn how to manage more systematically by designing standard menus of operations.     

Just-in-time: A cross-sectional plant analysis

This paper uses a data base of quantitative and qualitative plant-level cross-sectional data to analyze the relative performance of Just-in-time (JIT) and non-JIT plants operating in two distinct manufacturing industries: electronic components and auto-parts. A number of conjectures made by the literature concerning the relationship between JIT manufacturing and plant inventory holdings, costs and profits are tested. Consistent with many of these conjectures, the results suggest that JIT manufacturing at the plant level is associated with greater productivity in inventory usage, lower total and variable costs, but not fixed costs, and higher profits. The success of JIT plants along these dimensions is found to be related to the length of experience with JIT manufacturing, and process quality and leanness but unrelated to product quality, quality control or the extent of plant unionization.     

Model and analysis of integrated production–inventory system: The case of steel production

The study originated from an industrial case study in the field of steel production, but it presents a larger interest, as many other manufacturing fields have similar concerns (e.g. foundries, food, textile and paper industries). A significant phase of steel manufacturing is the product cooling (likewise, drying in paper and textile production, or maturing in food production). This phase may be completed in different ways, but (1) it must be carried out in the finished product warehouse and (2) it must meet both production optimisation and customer needs. The latter requirement acquires a strategic relevance in JIT environments. The present study proposes a mathematical model to find the optimal production schedule of steel billets, based on the relevant parameters of the productive system (set-up and processing times, demand profile). In the industrial case examined, the negative impact of holding costs on cash flows is also linked to the space required by the cooling process, which depends on the production schedule adopted. In other words, the finished product storage can be considered a part of the manufacturing cycle and impacts on it. In the case of steel plants operating in JIT environments, the warehouse must be promptly emptied and carefully managed to exploit the available space. Thus, the effect of inventory costs is examined in a production–inventory system with finite capacity, where products are made to order and share the same manufacturing facility. The study is completed by an experimental analysis to investigate the effect of variations in the relevant parameters of the problem.     

Cost Accounting and Performance Measurement in a Just-in-Time Production Environment

There are normative statements in the literature, backed up by case observations and anecdotal evidence, which indicate that manufacturing companies operating just-in-time (JIT) production management systems should also change their cost accounting systems and place greater reliance on non-financial performance indicators. This study provides empirical evidence suggesting that JIT manufacturing companies which have made some degree of modification to their costing system demonstrate higher performance than JIT companies which have not made changes. The results also suggest that greater use of non-financial performance indicators is associated with higher performance irrespective of the production management system adopted.     

Integrated production planning with sequence-dependent family setup times

This paper proposes an integrated optimization model of aggregate production planning (APP), family disaggregation planning, and family scheduling problems in hierarchical production planning (HPP) systems considering sequence-dependent family setup times. The model obtains the optimal production plan for each product type and product family in each period, together with the globally optimal production sequence of product families in all planning periods. The proposed model is tested with randomly generated experimental data consistent with what is prevalent in the manufacturing industry and its results are compared with those of the traditional HPP models. Our results show that the integrated model realizes greater cost savings.     

Pushing back the frontiers: management control and work intensification under JIT/TQM factory regimes

Drawing on primary and secondary sources the authors argue that the JIT/TQM manufacturing system intensifies work as a result of increased surveillance and monitoring of workers' activities, heightened responsibility and accountability, the harnessing of peer pressure within 'teams' and via 'customers', and the fostering of 'involvement' in waste elimination and the continuous improvement of the production process.     

A revised EMQ/JIT production-run model: An examination of inventory and production costs

Production-runs are an important cost minimizing scheduling and production planning activity. Commonly used classic lot-sizing models (i.e., economic manufacturing quantity or EMQ models) do not reflect current just-in-time (JIT) lot-sizing cost realities. The purpose of this paper is to present a cost comparison of the classic EMQ model and a revised EMQ/JIT model to show efficacy of a more cost inclusive model.     

A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry

This paper studies a solar cell industry scheduling problem which is similar to the traditional hybrid flow shop scheduling (HFS). In a typical HFS with parallel machines problem, the allocation of machine resources for each order should be scheduled in advance and then the optimal multiprocessor task scheduling in each stage could be determined. However, the challenge in solar cell manufacturing is the number of machines can be dynamically adjusted to complete the job within the shortest possible time. Therefore, the paper addresses a multi-stage HFS scheduling problem with characteristics of parallel processing, dedicated machines, sequence-independent setup time, and sequence-dependent setup time. The objective is to schedule the job production sequence, number of sublots, and dynamically allocate sublots to parallel machines such that the makespan time is minimized. The problem is formulated as a mixed integer linear programming (MILP) model. A hybrid approach based on the variable neighborhood search and particle swarm optimization (VNPSO) is developed to obtain the near-optimal solution. Preliminary computational study indicates that the developed VNPSO not only provides good quality solutions within a reasonable amount of time but also outperforms the classic branch and bound method and the current industry heuristic practiced by the case company.     

Markups in a dual labour market: The case of the Netherlands

We follow the production function approach to assess markups, which requires the estimation of the output elasticity of a flexible input. In the basic setup we estimate a structural value added production function, using temporary contract hours as flexible input. We find rather stable markups in the Netherlands in the period 2006–2016. We show that extending the flexible input incorrectly with fixed contract hours results in an increasing markup. Findings are robust to an alternative setup, in which a gross output production function is specified and materials are used as flexible input. Implications for applied work and policy are discussed.     

The adoption of radical manufacturing technologies and firm survival

The emergence of dramatically innovative, or radical, new manufacturing technologies can force pivotal and life‐threatening decisions for industry competitors. These technologies can represent a huge cost for adopting firms, but may also offer the chance to achieve competitive advantage through superior manufacturing. While prior research has considered a range of production process decisions (e.g., JIT, mass customization) and outcomes for end‐product technologies, little attention has been given to adoption decisions relative to core manufacturing technologies. This study examines an industry's adoption of major manufacturing technologies over several decades and demonstrates that two groups of contingencies related to adoption (e.g., timing and cumulative effects) have a significant impact on firm performance. Based on a sample of over 1,000 firms, the results provide insights into the effects of adoption timing and ‘manufacturing technology bundles’ on firm survival. We also find that adoption of manufacturing technologies prior to the inflection point of the estimated Bass diffusion curve for each technology leads to significant reduction in firm mortality. Thus, we are able to demonstrate the ability of the Bass model to predict the survival outcomes of firms facing manufacturing technology adoption decisions. The strategic implications of these pivotal decisions are considered. Copyright © 2008 John Wiley & Sons, Ltd.     

Flexible job shop scheduling with due window—a two-pheromone ant colony approach

Recently, the companies reduce the manufacturing costs and increase capacity efficiency in the competitive environment. Therefore, to balance workstation loading, the hybrid production system is necessary, so that, the flexible job shop system is the most common production system, and there are parallel machines in each workstation. In this study, the due window and the sequential dependent setup time of jobs are considered. To satisfy the customers’ requirement, and reduce the cost of the storage costs at the same time, the sum of the earliness and tardiness costs is the objective. In this study, to improve the traditional ant colony system, we developed the two pheromone ant colony optimization (2PH-ACO) to approach the flexible job shop scheduling problem. Computational results indicate that 2PH-ACO performs better than ACO in terms of sum of earliness and tardiness time.     

Product and Process Modularity's Effects on Manufacturing Agility and Firm Growth Performance

Modularity in product design has been hailed as a way to speed new product development (NPD), to reduce NPD cost, and to enhance customization possibilities for consumers. Modularity in process design may speed new product manufacturing setup times, reduce costs, and enhance the profitability of the lower volumes that customization often entails. However, empirical evidence is scarce that either product or process modularity—individually, jointly, or sequentially—actually produce these or other proposed benefits (e.g., performance growth). This study builds on general modular systems theory (GMST) by examining the theoretical relationship between product and process modularity and the effects of each on firm growth performance. Using structural equation modeling, partial versus complete mediation by manufacturing agility is also scrutinized. In one pair of models, product modularity and process modularity are separate direct antecedents to manufacturing agility, which is modeled to affect firm growth performance; in a second pair of models, product and process modularity are related antecedents to manufacturing agility, with product modularity preceding process modularity. Results from the best‐fitting model show that product modularity directly and positively affects process modularity, manufacturing agility, and firm growth performance. Process modularity was unrelated to manufacturing agility, and neither process modularity nor manufacturing agility predicted growth performance. Consistent with GMST, the study provides empirical evidence of the power of one element of a modular system to orchestrate a fit between a firm's product and manufacturing strategies and to directly drive system performance. Thus, modularity in product design is revealed as the key to understanding GMST effects concerning how changes in one system generate changes in other systems.     

Digital Machines,Space, and Time: Towards a Behavioral Perspective of Flexible Manufacturing

Recently, the diffusion of digital machines has further enhanced firms’ manufacturing flexibility, but also opened questions on potential challenges and implications in the production process. To respond to these timely issues, this study adopts a behavioral perspective and comparatively explores how four different types of digital machines—characterized by increasing degrees of manufacturing flexibility—affect the perception and use of space and time for routines within the production plant. To this end, 45 digital manufacturing machines, sampled across 14 firms in the British and Italian motorsport industry, were qualitatively observed and compared. A model emerges where four key mechanisms reshape (1) the interactive space around the machine, (2) the innovation activities performed in the machine space, (3) the time within activities involving the machine, and (4) the time perception. Such mechanisms mediate the relationship between manufacturing flexibility and firm performance. Further, data show how increasing digitalization in the manufacturing process enhances the establishment of new routines as flexible machines get introduced in the production. Finally, theoretical and practical implications related to fostering a behavioral perspective in innovation and operations management studies are discussed.     

Link between termination rates and retail prices in Namibia,Kenya and South Africa

This paper analyses the link between mobile termination rate reductions and retail prices. It draws on in-depth case studies of South Africa, Namibia and Kenya where regulators have reduced termination rates towards the cost of an efficient operator. To varying degrees these have all led to lower retail prices and significant market expansion. While retail prices in both Namibia and Kenya dropped following substantial termination rate reductions, the South African case demonstrates that termination rate reductions are not always passed on to consumers as is hoped by such regulatory interventions. In South Africa, it was only after the second reduction in March 2012 that smaller operators were able to reduce their off-net prices to a level that could tempt the subscribers to dominant operators to switch. All the case studies confirm nevertheless that retail prices do not go up in response to termination rates going down as contended by dominant mobile operators around the world. This is in contrast to a body of literature stating that termination rates and mobile retail prices constitute a two-sided market and that termination rate reductions will lead to a so-called “waterbed effect”.     

Coordinated supply chain scheduling

A mixed integer programming approach is proposed for a long-term, integrated scheduling of material manufacturing, material supply and product assembly in a customer driven supply chain. The supply chain consists of three distinct stages: manufacturer/supplier of product-specific materials (parts), producer where finished products are assembled according to customer orders and a set of customers who generate final demand for the products. The manufacturing stage consists of identical production lines in parallel and the producer stage is a flexible assembly line. The overall problem is how to coordinate manufacturing and supply of parts and assembly of products such that the total supply chain inventory holding cost and the production line start-up and parts shipping costs are minimized. A monolithic approach, where the manufacturing, supply and assembly schedules are determined simultaneously, is compared with a hierarchical approach. Numerical examples modeled after a real-world integrated scheduling in a customer driven supply chain in the electronics industry are presented and some computational results are reported.