Rolling horizon master production schedule performance: A policy analysis

In this paper, a simulation experiment has been developed to examine the combined influence of the design, inventory and environmental factors on the cost performance of a rolling horizon master production schedule. Specifically, a 2 5 factorial design was used to examine the effects associated with three rolling schedule design policies, one inventory policy and one environmental condition of forecast error on MPS cost performance. The study was based on actual data from a paint company. Results suggest that the choice of appropriate lot-size and inventory policies have a significant influence on MPS costs and that there are indeed important interactions between these policies and other design factors of a rolling schedule.     

Multi-item inventory model with quantity-dependent inventory costs and demand-dependent unit cost under imprecise objective and restrictions: A geometric programming approach

A multi-item inventory model with constant demand and infinite replenishment is developed under the restrictions on storage area, total average shortage cost and total average inventory investment cost. These restrictions may be precise or imprecise. Here, it is assumed that inventory costs are directly proportional to the respective quantities, and unit purchase/production cost is inversely related to the demand. Restricted shortages are allowed but fully backlogged. First, the problem is formulated in crisp environment taking the deterministic and precise inventory parameters. It is solved by both geometric programming (GP) and gradient-based non-linear programming (NLP) methods. Later, the problem is formulated with fuzzy goals on constraints and objectives where impreciseness is introduced through linear membership functions. It is solved using the fuzzy geometric programming (FGP) method. The inventory models are illustrated with numerical values and compared with the crisp results. A sensitivity analysis on the optimum order quantity and average cost is also presented due to the variation in the tolerance of total average inventory investment cost and total average shortage cost following Dutta et al., 1993, Fuzzy Sets and Systems, 55, 133-142.     

A new MRP/GT lot sizing heuristic: A simulation study

This paper studies the lot-sizing problem in Material Requirements Planning/Group Technology (MRP/GT) systems. A GT production cell is designed to produce many families of components. A major setup is required when switching from manufacturing one family of components to another family, and a minor setup is needed when switching from manufacturing a component type to another component type within the same family. Inventory holding cost is incurred if inventory level is positive, and inventory shortage cost is incurred if inventory level is negative, that is, backordering. The objective of the proposed lot-sizing problem is to minimize the sum of major and minor setup costs, holding and shortage costs, and regular production cost, and to meet simultaneously the demand requirements. The proposed problem is modelled into a linear integer program, a heuristic method to solve the problem is proposed, and a simulation experiment conducted to evaluate the performance of the proposed heuristic and some existing heuristics. The computational results show that the proposed heuristic is useful to reduce the total cost significantly over a wide variety of simulated environments.     

Effect of forecast errors on rolling horizon master production schedule cost performance for various replanning intervals

Master production schedules are usually updated by the use of a rolling schedule. Previous studies on rolling schedules seem to form the consensus that frequent replanning of a master production schedule (MPS) can increase costs and schedule instability. Building on previous research on rolling schedules, this study addresses the impact of overestimation or underestimation of demand on the rolling horizon MPS cost performance for various replanning frequencies. The MPS model developed in this paper is based on actual data collected from a paint company. Results indicate that under both the forecast errors conditions investigated in this study, a two-replanning interval provided the best MPS cost performance for this company environment. However, results from the sensitivity analysis performed on the MPS model indicate that when the setup and inventory carrying costs are high, a 1-month replanning frequency (frequent replanning) seems more appropriate for both of the above forecast error scenarios.     

On the impact of collaborative strategies for goods delivery in city logistics

Abstract

City logistics refers to the process of total optimisation of the logistics and transport activities in urban areas while considering economic, environmental, social and safety aspects. This paper considers a collaborative scenario for the urban goods transport planning and management as a way to reduce transport costs, congestion and environmental impact of this activity. An approach from the Operations Management field, using mathematical modelling, for tactical and operational decision-making is proposed to discuss and compare both collaborative and non-collaborative scenarios. This approach is validated using real data taken from the city of Bogotá, Colombia. Results put in evidence the quantitative benefits that can be achieved when collaborative logistics operations are implemented, represented in both transportation costs and environmental impacts. Although these results might not be surprising (like in the field of supply chain management), the contribution of this paper is centred in the fact that the impacts of collaboration in city logistics have not yet been quantified until now. This allows an ‘ex ante’ evaluation of the benefits of collaborative goods transport in cities.     

The effects of the warranty cost on the imperfect EMQ model with general discrete shift distribution

In this paper, we investigate the effect of the warranty cost on optimization of the economic manufacturing quality (EMQ). This is done for a deteriorating process where the production process shifts from the in-control state to the out-of-control state following a general discrete probability distribution. Once the production process goes out of control, the production process produces some defective items. The defective item cost includes reworking and warranty costs. Thus, in order to economically operate a production-inventory system with products sold under warranty, the tradeoffs among the production setup, inventory, and defective item cost, including the reworked cost before sale and the warranty cost after sale, needed to be analysed. This objective in this paper is to determine the production lot size while minimizing the total cost per unit of time per unit of time. Various special cases are presented. Two of them are extensions of results obtained previously in the literature. Finally, a numerical example is given which uses a discrete Weibull probability distribution. Sensitivity analysis of the model with respect to cost and time parameters is also performed.     

Bottleneck identification and ranking model for mine operations

Abstract

Mining has a long history of production and operations management. Considering the increasing complexity of reserves, declining metal grades, and worldwide price volatilities, mines have to operate more efficiently than ever. In recent years, companies have been adopting innovative solutions and technologies to reduce costs and remain competitive in the global market. Specifically, management of bottlenecks has been in the focus of the manufacturing industry for decades now. The mining industry has made significant advancements in process improvement tools using equipment, human, and asset tracking capabilities. However, to date, there is no holistic approach or system to identify and manage the bottleneck in the entire value chain of mining. This research proposes a new method to identify and rank the bottlenecks in a mine value chain. The method is applied in a coal mine and the results are presented in the case study.     

Development of demand pull type control methods: The design of block action production control methods to reduce throughput time and improve supply chain synchronization

In this paper the implementation of time based manufacturing strategies and pull type control systems in an organization manufacturing electrical switchgear built to customers individual requirements are discussed in detail. The concept of block control to synchronize the production time of all internally and externally sourced components and materials is also introduced in an attempt to simplify production control methods and reduce throughput time. Savings in time and cost are described during a twenty months period of restructuring. Foundations were laid for a second objective which is an attempt to gain some linkage between throughput time reduction and resultant production costs.     

Work & stress: Information

Abstract

The human and finacial costs of stress in the workplace have been extensively documented in the literature. The present study used a two-round Delphi methodology with 17 human resource managers from 17 medium-sized and large Canadian organizations. The main purposes of the study were to predict future policy and programme directions as well as expected benefits and constraints on organizations during the 1990s. This panel of experts predicated even greater stress in the workplace in large part due to greater (global) competition and greater resource constraints on organizations for programmes and services for their employees as well as management resistance to such directions. Organization will be challenged to identify cost effective means to prevent or, at least, to amelorate stress. Several practical ideas were generated by the panel for organizations to consider.     

A multiple buyer – supplier relationship in the context of SMEs’ digital supply chain management*

Abstract

By underlining the relevance of the use of ICTs, knowledge sharing and electronic markets for SMEs, it emerges the need for stimulating a debate on digitisation process of supply chain management (SCM). Electronic infrastructure in the service sector are reducing each kind of cost and improving multiply buyer–supplier relationships, facilitating negotiations and transactions. However, since the coordination costs are still high, the use of ICTs is limited. This phenomenon thus attracts the interests of scholars and practitioners. Although it still needs to further investigate. Especially, the optimal use of ICTs within SMEs’ SCM have not been studied yet. Therefore, by leveraging on four proxies: ICTs specialised human resources, knowledge sharing activities, buyer–supplier relationships, adoption of electronic markets this optimal was analysed via structural equation modelling based on a sample of 1254 SMEs operating in the service sector in Italy.     

A discussion on economic ordering policy of deteriorated item for vendor and buyer

Yang and Wee (Economic ordering policy of deteriorated item for vendor and buyer: an integrated approach. Prod. Plan. & Cont., 2000, 11(5), 474–480) proposed an ordering policy for a vendor--buyer integrated model. This note examines the cost component of Yang and Wee's model and gives some insight on the derivation of the holding cost function. We have discovered that their model violates the positive holding cost characteristic and the total quantity-equality characteristic. A proposal to eradicate the problem is given.     

The disassembly line: balancing and modeling,by S.M. McGovern and S.M. Gupta

This note addresses a problem faced by an actual firm. The problem is to decide on the optimal level of product quality. In performing the economic analysis to determine product quality level, the firm considers revenue, production costs, and research and development costs. However, this note shows that ignoring inventory costs in the analysis will lead to suboptimal product quality levels. Also, including inventory costs in the analysis will lead to reduced production lot sizes. Numerical examples are used to illustrate the results of the model.     

Resource smoothing: A cost minimization approach

From the available literature, there seems to be no defined approach to resource smoothing exercise except those attempted by Weist (1967, Management Science, 13, B359-B377) and Burgess and Killebrew (1962, Journal of Industrial Engineering, 13, 76-83). The aim of the smoothing exercise is to achieve optimal resource usage by avoiding high peaks and deep valleys in the project resource profile. The general approach has always been to move some activities with floats in the high peak regions to be started at a later date, and as this is done, the valleys will be filled to smooth the resource profile subject of course to time constraint. If this approach is followed as it is, it would be difficult to determine optimality especially when many resources are involved. A cost minimization approach is envisaged in the present study with no limitation on the number of resource inputs. In a situation where the resources are assumed to have the same value, the cost assigned to each of them should be similar. The method follows the general concept but with a difference; cost of the activity in question is considered. The exercise is continued until all the floats are exhausted. The optimum result would then be the one with the minimum cost profile. From examples used for the evaluation, the results obtained are comparable to those of the above two researchers, and some with better results in the majority of cases.     

Stockpiling supplies for disaster response: an experimental analysis of prepositioning biases

Abstract

Several relief organisations preposition supplies in preparation for disaster response. We show how the structure of prepositioning decisions resemble newsvendor decisions and how common newsvendor biases could affect prepositioning performance. To explore prepositioning biases, we run a behavioural experiment of a prepositioning problem with 20 practitioners from the humanitarian sector. Their task was to choose prepositioning quantities under different cost conditions and for supplies with different degrees of criticality. Results show that participants pull orders away from optimum (pull-to-centre) and follow the prior beneficiary demand realisation (demand chasing) regardless of cost and criticality conditions. However, the estimation of behavioural models reveals patterns hidden in averages, showing that participants weigh undersupply costs more for urgent supplies and urgency moderates demand chasing. A follow-up validation experiment manipulates the salience of urgent supplies by bundling them with non-urgent supplies in a portfolio. Results show that the portfolio strengthens these patterns, increasing the availability of urgent supplies. We offer practice implications of these findings for prepositioning activities and theory implications for inventory experiments in general.     

An optimal replenishment model for inventory items with normally distributed deterioration

This paper deals with the inventory replenishment problem for deteriorating items with normally distributed shelf life, continuous time-varying demand, and shortages under the inflationary and time discounting environment. The reasons of choosing normal are twofold: it is one of the most important probability phenomena in the real world due to the classical central limit theorem, and it is also one of the most commonly used lifetime distributions in reliability contexts. The problem is formulated as a dynamic programming model and solved by numerical search techniques. The solutions of the model determine the optimal replenishment schedule over a finite planning horizon so that the present worth of the future costs associated with the system is minimized. In the extensive experiments, we validate the model, demonstrate the optimal replenishment schedule and lot-size, and carry out a comparative study to ascertain its contribution. In addition, sensitivity analysis was provided to help identify the most crucial factors that affect system performance. The experimental result shows that the deteriorating problem solved by an appropriate model (i.e. the proposed normal model) can save the total cost up to 2% approximately. It also identifies that the magnitudes of purchase cost per unit and demand rate are the most significant parameters that affect the replenishment decisions and cost.     

Quantifying costs of forecast errors: A case study of the warehouse environment

Our study evaluates the impact of forecast errors on organizational cost by simulating a labor-intensive warehouse environment using realistic cost data from a case study. Unlike past studies that measure forecast error in terms of forecast standard deviation, our study also considers the impact of forecast bias, and the complex interaction between these variables. Two cases of organizational cost curves are considered, with differing and asymmetric structures. Results find forecast bias to have a considerably greater impact on organizational cost than forecast standard deviation. Particularly damaging is a high bias in the presence of high forecast standard deviation. Although biasing the forecast in the least costly direction is shown to yield lower costs, sensitivity analysis shows that increasing bias beyond the optimum point rapidly increases costs. ‘Overshooting’ the optimal amount of bias appears to be more damaging than not biasing the forecast at all. Given that managers often deliberately bias their forecasts, this finding underscores the importance of having a good understanding of organizational cost structures before arbitrarily introducing bias. This finding also suggests that managers should exercise caution when introducing bias, particularly for forecasts that inherently have large errors. These findings have important implications for organizational decision making beyond the simulated warehouse, as high forecast errors are endemic to many labor-intensive organizations.     

Development of an integrated information management model: A case of textile industry

For past two decades many organisations have tried to implement integrated information management systems for better production management based on co-ordination of information and therefore activities of different departments. Although Enterprise Resource Planning systems have been in the market for the past decade, many industries find it difficult to implement such systems due to the amount of work involved in streamlining the documentation, customisation and of high costs reported in implementation. An attempt is made through this paper to propose an integrated model, which can be easily understood by production personnel, with specific emphasis on the textile sector.     

Policy Incentives for Dangerous (But Necessary) Operations

In industries where firms perform dangerous (but necessary) operations, liability costs—due to potential harm to third parties—can be significant. Firms may therefore find it optimal to exit the market, and this may lead to an inefficiently low number of incumbents. A social planner can discourage exit by offering appropriately designed subsidies. Ex ante subsidies defray the costs associated with making operations safer (e.g., funds to subsidize the purchase of safety equipment). Ex post subsidies mitigate the financial damages caused by an accident (e.g., funds to defray the cost of cleaning up a toxic spill). We consider a model where (i) firms have private information about their ability to improve reliability and (ii) reliability investments are unobservable. We demonstrate that when the social value of reliability outweighs the benefit of increased competition, it is optimal to offer ex ante subsidies alone (i.e., to subsidize the cost of making operations safer). Conversely, when the benefits of competition outweigh the benefits of reliability, a combination of ex ante and ex post subsidies is optimal (i.e., not only to subsidize safer operations, but also to share the costs of a potential accident).     

Economic manufacturing quantities under conditions of learning and forgetting (EMQ/LaF)

Abstract

Abstract. It has been empirically observed that productivity improves as production continues due to system 'learning’, but that it deteriorates once the activity is stopped due to system 'forgetting’. Both learning and forgetting follow an exponential form with a 'doubling factor’ ranging between 0.75 and 0.98. We review and critique two previously proposed models, correct some minor errors in them, and expand one of them to accommodate a finite horizon. We also propose a new model that is more in harmony with the established learning function, for the determination of the optimal number and size of the lots in the finite and infinite horizon. The methodology used throughout is dynamic programming. We investigate the impact of all three models on the optimal lot sires and their costs, and establish the functional relations between the total cost and the various factors affecting them.     

Analysis and Management of Periodic Review,Order‐Up‐To Level Inventory Systems with Order Crossover

In this article, we investigate the (R, S) periodic review, order‐up‐to level inventory control system with stochastic demand and variable leadtimes. Variable leadtimes can lead to order crossover, in which some orders arrive out of sequence. Most theoretical studies of order‐up‐to inventory systems under variable leadtimes assume that crossovers do not occur and, in so doing, overestimate the standard deviation of the realized leadtime distribution and prescribe policies that can inflate inventory costs. We develop a new analytic model of the expected costs associated with this system, making use of a novel approximation of the realized (reduced) leadtime standard deviation resulting from order crossovers. Extensive experimentation through simulation shows that our model closely approximates the true expected cost and can be used to find values of R and S that provide an expected cost close to the minimum cost. Taking account of, as opposed to ignoring, crossovers leads, on average, to substantial improvements in accuracy and significant cost reductions. Our results are particularly useful for managers seeking to reduce inventory costs in supply chains with variable leadtimes.