Mathematical models of inventory typically include the three inventory associated costs of surplus, shortage and ordering. These classic inventory models are then analysed so as to choose inventory ...parameters that usually minimise the total cost of operating the inventory system being investigated.
Unfortunately, classic inventory models do not provide a meaningful basis for analysing many real and increasingly important practical inventory problems and situations. It is therefore not surprising that over recent years, several authors have discussed these issues in broad terms and suggested that a new paradigm needs to be developed.
This paper develops some specific aspects of this discussion. In particular, the paper identifies a range of inventory problems that are not covered appropriately by traditional inventory analysis. One of these is to design responsible inventory systems, i.e. systems that reflect the needs of the environment. The paper then examines the importance of inventory planning to the environment in greater detail. For example, packaging is important, not only because of its costs and the protection that it provides to the inventory items, but also because of its eventual effects on the environment in terms of the use of resources and potential landfill. For similar reasons, waste, which can result from poor inventory management, is highly important. The location of stores is important because location affects transport costs. Thus the influence of the secondary aspects of most inventory models; packaging, waste and location are important but, even more important are the inter-relations with the total system. In particular, the location of the manufacturing plants and the effect that inventory planning has on the logistics chain, potentially have considerable environmental implications. Inventory is part of a wider system.
However, until the cost charged for an activity reflects the true environmental cost of that activity, it is likely that decisions will be made on the basis of erroneous data. In that situation, we are faced with either determining the environmental cost of specific actions or to use environmental costs that are somewhat contrived; in which case it may be more sensible to use very different performance measures and models. The paper discusses these ideas and ways in which inventory policies may reassure us with our environmental concerns.
An approach similar to Salameh and Jaber (2000) has been used in this paper to produce an optimal production/order quantity that takes care of imperfect processes. An imperfect inspection process ...(Raouf et al., 1983) is utilized to describe the defective proportion of the received lot. That is, the inspector may commit errors while screening. The probability of misclassification errors is assumed to be known. The inspection process would consist of three costs: (a) cost of inspection (b) cost of Type I errors and (c) cost of Type II errors. The defective items, classified by the inspector and the buyer would be salvaged as a single batch that is sold at a lower price. A mathematical model is developed to depict this scenario. Numerical examples are provided to illustrate the solution procedure.
The Economic Order Quantity, EOQ, model has been popular among academicians and practitioners for decades. Despite the many variants of the EOQ that have appeared in the literature to fine-tune it to ...reality, it still has limitations. A major one is that it does not take into account the hidden costs inherent in inventory systems. Some of these costs relate to sustainability issues including environmental, social labor, and economic effects.
This paper considers some of these costs, referred to as the exergetic costs, and estimates them using the Extended Exergy Accounting, EEA, approach. Extended Exergy Accounting assigns equivalent exergetic values to capital, labor and environmental remediation costs of a system. The analysis combines the classical exergy analysis with the sustainability factors, which are the labor, capital and environment. The paper uses an exergetic model to determine the EOQ inventory policies for three firms operating in the USA, Germany and China. The results show that the EOQ is different for the three firms because the equivalent exergy of capital, labor and environment remediation costs is different in each country.
•Uses the Extended Exergy Accounting (EEA) approach to analyze inventory systems.•Combines the classical exergy analysis with sustainability.•Results show that the EOQ differs from country to country.
An activity matrix (AM) shows the activities that transform an organizationas inputs into outputs. The inputs are the system targets and the materials, energy and other resources that are used to ...achieve these. The outputs are the system performance expressed in terms of production, quality, profit, environmental performance, waste, etc. Performance may be measured against the financial, environmental, technical, social or other system targets.
•Modifies EMQ to include some operational, environmental and social costs.•Compares EMQ and JIT models using the second law of thermodynamics.•JIT is more expensive when worker stress and entropy ...costs are considered.
Just-In-Time (JIT) suggests that inventory is a waste and should be reduced. However, under some conditions, smaller and more frequent shipments can generate more waste, consume more resources and increase congestion in a supply chain rendering the JIT policy less effective. This paper first modifies the standard economic manufacture quantity (EMQ) models by including within them the costs of transportation, worker stress, process quality, energy, and greenhouse gas emissions. Then, it uses the second law of thermodynamics to calculate the entropy generated in the modified EMQ and JIT models, using entropy as a measure of system sustainability. To make the comparison meaningful, the EMQ model is modified to capture some of the costs that will work for and against EMQ and JIT. The modification then adds an entropic component to the cost functions of EMQ and JIT to capture the costs of disorder (entropic) that classical inventory analyses seldom include. The results show that when worker stress and entropy costs are considered, a JIT policy can be more expensive to operate than an EMQ policy.
In this paper, the forgetting slope is shown to be mathematically dependent on the following factors:
1.
(1) the learning slope,
2.
(2) the quantity produced to date, and
3.
(3) the minimum break at ...which total forgetting occurs.
It is also shown that it is possible to determine the value of the forgetting rate once the curve's mathematical form is assumed. This answers some potential considerations inherent in the arbitrary assumption of forgetting rate. This paper also investigates the effects of learning and forgetting on both the optimum production quantity and the minimum total inventory system cost.
An activity matrix (AM) shows the activities that transform an organization’s inputs into outputs. The inputs are the system targets and the materials, energy and other resources that are used to ...achieve these. The outputs are the system performance expressed in terms of production, quality, profit, environmental performance, waste, etc. Performance may be measured against the financial, environmental, technical, social or other system targets.
A concurrent enterprise view is used to represent the manufacturing system activities and the paper examines how an AM may be used to represent and design systems. Two kinds of AM are examined; an unconstrained activity matrix and an input–output activity matrix (IOAM). With an unconstrained AM, the system designer chooses system outputs (attributes or requirements) intuitively. This provides great flexibility and allows e.g. the social and organisational implications of proposed changes to be investigated. The inputs are not formally stated. Although a systems designer normally focuses on identifying the stages of a product life cycle and analysing their impact on the system's outputs, the main emphasis of the paper is on the IOAM and its use to represent the transformation of an organization’s inputs into outputs. The input–output representation developed in the paper is used to examine manufacturing and logistics systems. First, the IOAM is used to represent a manufacturing system (as one tier of a logistics chain) and its performance. Secondly, the IOAM representations may be derived for a multi-tier system to represent its production, economic and environmental performance.
The paper describes a methodology to help systems analysts identify and prioritise an organisation's manufacturing and logistics problems and determine the changes that the organisation needs. The ...problems and associated investigations form the research and implementation agendas. The methodology considers the manufacturing system functions of a company to be part of a concurrent enterprise. It then uses the concurrent enterprise model in conjunction with an unconstrained Activity Matrix (AM), which shows the activities of the system that converts physical inputs and plans (stated or implied) into the important variables and system performance measures which are called attributes.
The methodology uses an Activity Matrix (AM) to produce a Problem Matrix (PM). From this, a Tentative Research Matrix (TRM) is produced, and subsequently a Research Matrix (RM) is developed. Then the RM activities are prioritised to create the Research Agenda (RA).The sequence of steps is AM⇒PM⇒TRM⇒RM⇒RA.
The research agendas methodology is developed in the broad fields of logistics and production and operations management. The paper tests the proposed methodology using the function of production planning and control.
•Presents a methodology for deriving Research Agendas (RA).•Sets the methodology in the context of other RA studies.•Checks the feasibility of the methodology.•Checks the methodology by deriving a RA for PPC (Production planning and control).
•An EPQ model based on the laws of thermodynamics is developed.•Model employs exergy to improve efficiency.•Focuses on the three pillars of sustainability and computes their costs.•Uses the amount of ...consumed exergy as a sustainability indicator.•A sustainable strategy can be profitable.
Businesses strive to be sustainable because of internal and external pressures. To examine sustainability, firms may use different methods of analysis. Extended Exergy Accounting (EEA) - a resource based evaluation method - is such a tool used to examine environmental, social, and economic sustainability. This paper re-examines the economic production quantity (EPQ) model, in an attempt to reflect the needs of sustainability. The paper uses EEA and the laws of thermodynamics to measure the sustainability of a production-inventory system and finds that in some situations sustainability can be profitable. EEA measures the value of a commodity, based on the consumption of the natural and physical resources as opposed to the classical EPQ model, which uses monetary cost. Measuring the exergy consumed during the production of a commodity shows that the exergetic model developed can deliver better sustainability and profitability than the classical EPQ. This should further encourage companies to move towards sustainable strategies. The results suggest that governments, individuals and other organizations should encourage companies to move towards sustainable strategies.
Learning curve theory has been widely used as a managerial tool to describe and model product and process improvement. This paper investigates a three-level supply chain ...(supplier–manufacturer–retailer) where the manufacturing operations undergo a learning-based continuous improvement process. Improvements in the manufacturer’s operation are characterized by enhanced capacity utilization, reductions in set-ups times, and improved product quality through the elimination of rework. As a result of these continuous improvements, the manufacturer can justify a production policy that is based on more frequent, smaller lot size production. For this production policy to be practical and not sub-optimal to the supply chain, the manufacturer must integrate its lot-sizing models with the replenishment policies of its upstream raw material suppliers and the demand requirements of its downstream customers (retailers). Mathematical models that achieve chain-wide lot-sizing integration are developed and solution procedures for the models are illustrated by numerical examples. The results demonstrate that learning-based improvements in set-up time and rework allow retailers to order in progressively smaller lot sizes as the manufacturer offers larger discounts and profits and that the entire supply chain benefits from implementing learning-based continuous quality improvements. The results also demonstrate that forgetting effects lead to increases in supply chain costs.
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