Abstract: In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.
Abstract: Due to shortening product and technology lifecycles, many companies use standardization approaches in product development and factory planning to reduce costs and time to market. Unlike large companies, where modular systems are already widely used, small and medium-sized companies often show a much lower degree of standardization due to lower scale effects and missing capacities for the development of these standards. To overcome these challenges, the development of industry sector specific standards in cooperations or by third parties is an interesting approach. This paper analyzes which branches that are mainly dominated by small or medium-sized companies might be especially interesting for the development of factory standards using the example of the German industry. For this, a key performance indicator based approach was developed that will be presented in detail with its specific results for the German industry structure.
Abstract: One of the most famous techniques which affect the
efficiency of a production line is the assembly line balancing (ALB)
technique. This paper examines the balancing effect of a whole
production line of a real auto glass manufacturer in three steps. In the
first step, processing time of each activity in the workstations is
generated according to a practical approach. In the second step, the
whole production process is simulated and the bottleneck stations
have been identified, and finally in the third step, several
improvement scenarios are generated to optimize the system
throughput, and the best one is proposed. The main contribution of
the current research is the proposed framework which combines two
famous approaches including Assembly Line Balancing and
Optimization via Simulation technique (OvS). The results show that
the proposed framework could be applied in practical environments,
easily.
Abstract: A novel concept to balance and tradeoff between
make-to-stock and make-to-order has been hybrid MTS/MTO production context. One of the most important decisions involved in
the hybrid MTS/MTO environment is determining whether a product
is manufactured to stock, to order, or hybrid MTS/MTO strategy. In this paper, a model based on analytic network process is developed to tackle the addressed decision. Since the regarded decision deals with
the uncertainty and ambiguity of data as well as experts- and
managers- linguistic judgments, the proposed model is equipped with
fuzzy sets theory. An important attribute of the model is its generality due to diverse decision factors which are elicited from the
literature and developed by the authors. Finally, the model is validated by applying to a real case study to reveal how the proposed
model can actually be implemented.