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The purpose of this study is to propose a new dynamic model of a production-inventory control system. The objective of the new model is to maximise the flexibility of the system so that it can be used by decision makers to design inventory systems that adopt various strategies that provide a balance between reducing the bullwhip effect and improving the responsiveness of inventory performance.

The proposed production-inventory control system is modelled and analysed via control theory and simulations. The production-inventory feedback control system is modelled through continuous time differential equations. The simulation experiments design is conducted by using the state-space model of the system. The Automatic Pipeline Inventory and Order-Based Production Control System (APIOBPCS) model is used as a benchmark production-inventory control system.

The results showed that the Two Automatic Pipelines, Inventory and Order-Based Production Control System (2APIOBPCS) model outperforms APIOBPCS in terms of reducing the bullwhip effect. However, the 2APIOBPCS model has a negative impact on Customer Service Level. Therefore, with careful parameter setting, it is possible to design control decisions to be suitably responsive while generating smooth order patterns and obtain the best trade-off of the two objectives.

This research is limited to the dynamics of single-echelon production-inventory control systems with zero desired inventory level.

This present model is an extension and improvement to Towill’s (1982) and John et al.’s (1994) work, since it presents a new dynamic model of a production-inventory control system which utilises an additional flow of information to improve the efficiency of order rate decisions.

The learning effect is well established in the repetitive performance of industrial tasks and it is essential that production management be aware of the potential for improved performance (measured by dynamic gain) and the rate at which this may be achieved/measured by the time constraint. Performance and contingency logging and trend modelling should be part of the management information system so that the appropriate learning curve can be established and stored in the databank for future planning purposes. The application of the learning curve to batch production shows that performance slippage caused by elapsed time between batch completions is a significant factor in manufacturing time increase, and, hence, labour costs. This should be allowed for when optimising batch production policy, forecasting deliveries, and

Reviews the dynamic operation of supply chains and reaches some simple conclusions for reducing demand amplification, which consequently attenuates swings in both production rates and stock levels. The results are based on one particular supply chain, for which the use of systems simplification techniques has generated valuable insight into supply chain design. Although different strategies are compared for reducing demand amplification as witnessed by one particular supply chain model, the conclusions are nevertheless thought to have wide application and, indeed, implication. Comments in depth on the significance of the simulation results for the demand chain as a whole, and for the role of an individual business within the chain. In the first instance, supply chain integration, and in particular free exchange of information, is a prerequisite for progress. In the second case, shows that reduction in lead times throughout the supply chain via JIT is similarly beneficial. Clearly pinpoints the limitation to supply chain improvement which can be obtained as a result of using JIT alone. This can be an expensive and ongoing process of improvement with many spin‐off benefits. Nevertheless, shows that the improvement possible by JIT operation of an individual business can be negated by the failure to design and manage the supply chain dynamics as a total system. The message for an individual business is thus quite specific. Not only must lead times be reduced via JIT, but also the business must seek to be part of the right supply chain, if it is to remain competitive and stable.

Aims to discuss the basic strategy taken by a specific manufacturer. States supply chain structures influence, directly, the supply chain inventory as a measure of performance. Examines the difference in the supply chain in relation to the manufacturer’s strategy to the product.

Outlines cost benefits for information system implementation using electronic data interchange as the enabling tool. Highlights rarely cited on‐cost benefits through the examination of supply chain dynamics, and their relative reductions created through increased stability. Examines two business re‐design strategies, namely lead time reduction via information systems implementation and information integration in the form of actual customer demand fed forward to all supply chain members. Highlights global integrated logistics information systems and describes their role in overall supply chain system optimization.

In this paper, the joint replenishment problem is modeled for a two-level supply chain consisting of a single supplier and multiple retailers that use the vendor-managed inventory (VMI) policy for several products. This paper aims to find the optimal number of products to order in both policies, the optimal times at which each retailer orders the products in the traditional policy and the optimal times at which the supplier orders the product in the VMI policy.

The problem is first formulated into the framework of a constrained integer nonlinear programming model; then, the problem is solved using a teacher-learner based optimization algorithm. As there are no benchmarks available in the literature, a genetic algorithm is used as well to validate the results obtained.

The solutions obtained using both the algorithms for several numerical examples are compared to the ones of a random search procedure for further validation. A real case is solved at the end to demonstrate the applicability of the proposed methodology and to compare both the policies.

The paper does not have any special limitations.

The study has significant practical implications for the sellers and for the suppliers who have to get the most profit. Also, satisfying the constraints make decision more complicated.

This paper has two main originalities. The authors have developed the model of the joint replenishment problem and have contributed in the problem-solving process. They have used a new meta-heuristic and then compared it to a classic one.

This monograph examines research needs in computer aided production management (CAPM). Recommendations for future research and its organisation are made. The monograph is based on an in‐depth study of current CAPM practice in a varied sample of 33 companies. The study conclusions confirm many existing beliefs. Many companies are paying inadequate attention to the necessary prerequisites for successful CAPM implementation. The prerequisites change as the extent of CAPM system integration increases. Organisational rather than implementation issues dominate as integration increases. The proposed research would bring together existing knowledge of best CAPM practice to form methodologies for the audit, design and implementation of CAPM systems. The aim is to reduce the time‐span of the learning curve required for successful CAPM integration. The methodologies need to be specific to particular industrial sectors.

The purpose of this paper is to discuss the theoretical foundations, development, and application of the quick scan audit methodology (QSAM) for comparative evaluation of supply chains via uncertainty codification and material flow assessment.

Charts the evolution of QSAM via the Parnaby concept of a manufacturing system leading to a control model representation of a value stream. Monitoring in process and critical interface material and information flows provide the substantive data to evaluate supply chain health. The authors show how QSAM satisfies the six desirable attributes previously established as advantageous when value stream auditing.

Basing QSAM on this particular systems approach readily leads to transferability of approach to new market sectors and new companies within the same sector. It ensures comparability via uncertainty levels to be established. Hence, using statistical cluster analysis “best practice” may be identified and annotated.

There may yet be specific supply chain regimens where uncertainty codification is insufficient to reach a definitive conclusion. However, QSAM is now sufficiently mature that it has been applied successfully and widely beyond its original systems‐friendly European automotive sector.

A systematic, non‐industry‐specific audit method based on systems modelling builds confidence into comparability studies and identification of “exemplars” exhibiting best practice. The importance of understanding and satisfying the expectations of the four “players” in the QSAM balanced scorecard is discussed and exemplified.

QSAM is an original contribution which fits well into the spectrum of excellence measurement techniques. The two established extremes are vertical case studies (European style) and horizontal surveys (US style). QSAM brings together certain strengths of each so that the whole is greater than the sum of the parts.

Compares the bullwhip properties of a vendor managed inventory (VMI) supply chain with those of a traditional “serially‐linked” supply chain. The emphasis of this investigation is the comparative impact the two structures have on the “bullwhip effect” generated. Particular attention is paid to the manufacturer's production ordering activities as demonstrated using a simulation model based on difference equations. Documents and considers each of the four important sources of the bullwhip effect in turn. The analysis shows that with VMI implementation two sources of the bullwhip effect may be completely eliminated, i.e. rationing and gaming or the Houlihan effect, and the order batching effect or the Burbidge effect. VMI is also significantly better at responding to rogue changes in demand due to the promotion effect or to price induced variations. However, the effect of VMI on demand signal processing induced bullwhip or the Forrester effect is less clear cut. Concludes that on balance VMI offers a significant opportunity to reduce the bullwhip effect in real‐world supply chains.

The purpose of this paper is to examine the impact of applying two classical controller strategies, including two proportional (P) controllers with two feedback loops and one proportional–integral–derivative (PID) controller with one feedback loop, on the order and inventory performance within a production-inventory control system.

The simulation experiments of the dynamics behaviour of the production-inventory control system are conducted using a model based on control theory techniques. The Laplace transformation of an Order–Up–To (OUT) model is obtained using a state-space approach, and then the state-space representation is used to design and simulate a controlled model. The simulations of each model with two control configurations are tested by subjecting the system to a random retail sales pattern. The performance of inventory level is quantified by using the Integral of Absolute Error (IAE), whereas the bullwhip effect is measured by using the Variance ratio (Var).

The simulation results show that one PID controller with one feedback loop outperforms two P controllers with two feedback loops at reducing the bullwhip effect and regulating the inventory level.

The production-inventory control system is broken down into three components, namely: the forecasting mechanism, controller strategy and production-inventory process. A state-space approach is adopted to design and simulate the different controller strategy.