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Inventory control problems often result in record and physical count discrepancies which may ultimately lead to higher than preferred inventory levels. Conversely, accurate inventory records result in lower inventory investment and are the foundation for forecasting, ordering, tracking, vendor evaluation, and dead stock administration programmes. Guidelines, based on general systems theory, to identify the presence of inventory control problems in both physical operations and information systems areas are presented. Next, procedures to correct control problems are discussed. These include the formation of a permanent taskforce, corporate‐wide education on the importance of record accuracy, and the development of a general management plan based on sound principles for effective inventory control. Recent experiences within a telecommunications company having inventory control problems are used as a case example to illustrate specific points.

This article examines inventory control problems in developing countries using the results of a field study conducted in the industrial sector of a developing country. It is shown that ineffective inventory control is a major problem faced by industries in developing countries and that even the very basic inventory control concepts and techniques are not used by the majority of the companies studied. Due to the heavy reliance on imported industrial raw materials and parts, and the endemic bureaucratic delays and associated communication problems in developing countries, order lead times cannot be computed with any degree of accuracy. Therefore manufacturers attempt to overcome the uncertainty by carrying excessive amounts of buffer stocks.

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.

This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO).

The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation.

The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions.

This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level.

PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

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.

The paper's purpose is to provide a method of reducing inventory costs in multi‐product and multi‐nodes supply chains (SC).

The proposed approach is based on applying the classical inventory control models and simulation. This is a two‐stage approach in which inventory cost reduction in the SC occurs as a result of the appropriate selection of inventory control policies by its members.

Cost reduction in the whole SC may occur as a result of an appropriate choice of inventory control policies in every node. SC members can learn which inventory control policies should be applied. Results of the learning process are closely connected with a kind of collaboration between chain nodes. The best results of the whole system can happen with a simultaneous deterioration of operation of its component elements. Therefore, losses which occur in some chain members as a result of collaboration should be compensated.

This approach does not offer an optimal solution. The authors do not know how far they are from an optimal solution. The approach should be tested for more complicated SC. The authors have not studied the strategy in which SC cells negotiate the level of their inventories.

SC cells should apply a local cooperation strategy. When the cost of the whole SC decreases, the cost in particular nodes may significantly increase. The start of collaboration in the SC can cause a deterioration of results in some companies; therefore this loss should be compensated.

The paper presents the development of a framework in which an application of different policies of inventory control and application of different collaboration strategies in the SC are studied. The framework enables the use of classical inventory control models in a coordinated manner, and SC members decide which policies should be applied only on the basis of earlier collected experiences.

Computerising inventory control procedures is usually an attempt to gain better control over stock availability. The effectiveness of the procedures depends on the time delays imparted by such events as order processing and delivery. Through these time delays, much of a finished goods physical distribution system is linked together through the inventory control procedures. Changing the length of any one time element through changes in inventory stocking rules, order processing methods or selected transportation services impacts on the economics of the entire physical distribution system. Little is understood about the effects of time change in such complex systems. In this article, the actual computer inventory control procedures of a chemical company were computer simulated. Physical distribution system design decisions and their associated time delay effects were explored by interrogating the model. Surprising effects were discovered, some of them being counter‐intuitive to what simple theory would predict. Management guidelines were provided as to the system‐wide economic consequences of change in individual elements of a physical distribution system.

In order to ensure that an inventory system is performing correctly, management must continually monitor the system and take corrective action as necessary. Only a few previous articles have suggested techniques for monitoring and diagnosing the performance of a reorder point system. Uses statistical process control charts to monitor the systems performance on an ongoing basis. The proposed system is triggered by unplanned stockouts or by a periodic review of each item′s inventory turnover rate. The system then systematically analyses the stockout and the control charts and identifies the causes, which can be fitness‐related and/or operations related. Problems can be quickly diagnosed and corrective action taken so the reorder point system will perform as intended.

Key components of the logistics mix are described in an effort to create an understanding of the total logistics concept. Chapters include an introduction to logistics; the strategic role of logistics, customer service levels, channel relationships, facilities location, transport, inventory management, materials handling, interface with production, purchasing and materials management, estimating demand, order processing, systems performance, leadership and team building, business resource management.

For a manufacturing company, inventory control and management is crucial to ensure smooth production and sustainable sales performance, as well as preventing stockout that will result in customer switch to competitors. This paper aims to examine the effectiveness of cycle count activities, one of the inventory control tools to manage inventory. Beside, this study also wishes to identify any loopholes in practices and procedures in inventory control of companies.

One of the lubricant manufacturing companies in Malaysia was selected as a case study and mixed method data collection of document analysis and observation were used. The analysis and examination was conducted by using Committee of Sponsoring Organization of the Treadway Commission Framework 2013 as guidance.

This study found that problems in inventory control can be caused by inconsistency of practices due to incomplete or absent standard operating procedures. Furthermore, no segregation of duties and excessive reliance on one person to conduct many tasks will lead to human error and fraud.

This paper enhances the theoretical understanding on the inventory control and management system applied in the manufacturing organization particularly. However, frequent changes of the management in the organization of the case study make the study difficult to obtain consistent information. Not all standard operating procedures were revised or updated and available for examination. In addition, some of the reports needed for investigation are confidential and requests to observe and scrutinize information from those documents are denied by the company. Thus, more in-depth analysis and verification on the issues of interest were unable to be conducted.

This study provides an indicator that cycle count activities need to be conducted frequently on a regular basis so that the physical inventory and recording system are accurate. Cycle count activities also must involves various related departments in the company in which regular training is essential to ensure employees are aware and understand their responsibility and accountability on the inventory.

This study is original as it focuses on the inventory control management of one of the largest lubricant manufacturing in Malaysia, particularly on cycle count activities which is scare in literature. Furthermore, the company allows research access to the documents and operations conducted in the company, which is usually difficult to obtain from many companies.