company, facing growing backorders, repeated failures, complaints and
other problems in performance, losses profits and time. Therefore,
mangers need to put and solve complex strategic alignment issues
concerning how business processes can be improved as well as what
results would be achieved by such strategies. Present paper uses
customer order decoupling point and inventory control policy as primary
managerial tasks for the alignment of production and sales processes.
The solution of these tasks ensures production line balance, supports
reliable and efficient customer relationships, and, in particular,
orders fulfilment. To verify the solutions’ ability to shorten costs and
sales loss, computer-aided discrete-event simulation is chosen as
scenario analysis tool. In the paper, Arena simulation models represent
manufacturing system in make-to-stock manner according to customer order
decoupling point and implement periodic inventory management policies
with backordering and loss of sales, such as line balancing and basic
stock, checking threshold, and combination thereof. The models are
managerial tool for decision-making, providing verification of business
strategies by parametrical study of non-stationary customer demand.
Keywords: DISCRETE-EVENT SIMULATION, PRODUCTION, SALES, INVENTORY MANAGEMENT, PROBLEM SOLVING.
Companies have to handle with a variety of challenges in their production and sales processes in fast-changing business environment (Kulkarni and Prashanth, 2012). Managers look for many events and external factors to identify risks and managerial problems. Generally speaking, problems are seen as failures or breakdowns, economic lags, backlogs of orders, gaps between planned and actual values of performance indicators, collection of criteria and alternatives, separated knowledge, and different constructions and perceptions of "real world”, etc. (Hicks, 2004). During control of economic facilities managers declare often that a problem has arisen at a situation, when they regard facility’s state as abnormal, unacceptable or undesirable, and see that indicators of efficacy, effectiveness and efficiency are below the necessary or expected level. This type of problems might be called as "negative problem”. If system saves its good or normal state that was previously defined so that it caused mainly unreasonable rising of the objectives of system’s activity, then agents deal with the type of "positive problem”. The first type of problems usually leads to losses of profit due to expenses for elimination of mismatches, while the second type may cause losses owing to large expenses for conformance to excessive objectives.
The lack of sophisticated problem-solving approaches, techniques and tools restrains company's ability to tackle crucial issues and tasks at the right time and the lowest cost under rapidly changing customer demand. Many researchers consider computer simulation is one of the well-known efficacious tools for problem solving.
Understanding of complex problems, their roots and effects on performance and ready deliveries requires "what-if” scenarios that can be supported by simulation techniques (Robinson, 1994). It is important to synchronize business processes and align corresponding strategies of marketing, production, sales and logistics. First of all, managers have to consider company’s production and sales processes from push/pull views of logistics and Customer Order Decoupling Point, CODP, and types of production system (van der Vorst, Beulens and van Beek, 2005). Also they need to choose or modify inventory policies, e.g. (R,Q), (s,Q), (s,S), (R,S), (R,s,S) etc., and set parameters for them that would lead to balancing production line and inventory and decreasing costs, and meeting customer demand (Axsäter, 2007; Estelles-Miguel et al; Rabta and Aissani, 2005; Rosetti et al, 2008; Wisner et al, 2008). Simulation techniques can help to overcome such challenges due to selective or combined applying of a wide variety of business approaches, policies and strategies and keeping other specifics of production and sales processes in dynamic non-stationary environment.
So, it’s important to find out, which inventory management policies should be selected for the manufacturing system under varying customer order flow at planning period. Because of non-stationary order flow and unstable operations mode, the policies cannot contain constant values of parameters, which indicate when and how much to produce goods to fulfil new orders, backorders, and replenish stock.
Thus, this study is devoted to verification of system capacity and selective or combined inventory management policy responsible for alignment of production and sales processes, ensuring line balance, lowest inventory costs and loss of sales. The paper proposes utilizing simulation techniques and tools for scenario analysis. Therefore, study’s objectives are to develop discrete-event simulation models of production and sales processes for make-to-stock manufacturing system, based on the principles of basic stock and threshold checking, incorporating sales patterns.
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