An optimal batch size for an imperfect production system with quality assurance and rework

We consider a manufacturing system which receives raw material from a supplier, processes it, and delivers it to the customer periodically. The system considered is imperfect and produces defectives at a constant rate. The finished product can only be delivered if the whole lot is quality-certified. Hence, defectives have to be reworked, and the whole lot quality-checked within the cycle. Three different scenarios are considered, viz. (a) a single lot of raw material for multiple lot of finished product and delivery of the product in multiple instalments, (b) a single lot of raw material for a multiple lot of finished product and delivery of the product in a single instalment, and (c) lot-for-lot and delivery of finished product in single instalment. A total cost equation is developed for each model, and the optimal ordering quantities are evaluated. The results found are encouraging and quite simple to use for practical purposes.     

Operations planning in a supply chain system with fixed-interval deliveries of finished goods to multiple customers

Raw material ordering policy and the manufacturing batch size for fixed-interval deliveries of finished goods to multiple customers play a significant role in economically managing the supply chain logistics. This paper develops an ordering policy for raw materials and determines an economic batch size for a product at a manufacturing center which supplies finished products to multiple customers, with a fixed-quantity at a fixed time-interval to each of the customers. In this model, an optimal multi-ordering policy for procurement of raw materials for a single manufacturing system is developed to minimize the total cost incurred due to raw materials and finished goods inventories. The carried over inventory of finished goods from the previous cycle is used as initial finished goods inventory, resulting in shifting the production schedule ahead for the next cycle. A closed-form solution to the problem is obtained for the minimal total cost. The algorithm is demonstrated for multiple customer systems.     

Pull-type manufacturing systems with multiple product types

A multiple-product facility consisting of a manufacturing process and a finished product warehouse for several types of products is considered. An (R, r) continuous-review inventory control policy is applied to each type of product in the warehouse. The demand arrival process of each type is assumed to be Poisson. The processing times and the set-up times are arbitrarily distributed. We have developed an iterative procedure to approximately compute the average inventory level of each product in the warehouse under different priority schemes     

A fuzzy approach to process plan selection

Process planning is the systematic determination of the detailed methods by which parts can be manufactured from raw material to finished product. In a real manufacturing environment, usually several different parts need to be manufactured in a single facility sharing constrained resources. The existence of alternative process plans for each part makes the selection of process plan a very important issue in manufacturing. The objectives in process plan selection might be imprecise and conflicting. In this paper, a fuzzy approach is used to deal quantitatively with the imprecision of the process plan selection problem. Each process plan is evaluated and its contribution to shopfloor performance is calculated using fuzzy set theory. A progressive refinement approach is used to first identify the set of process plans that maximize the contributions, and then consolidate the set to reduce the manufacturing resources needed.     

System modelling for economic raw material selection

A system simulation method for economic raw material selection is presented, based on a realistic example. The total cost considered in raw materials selection is deemed to include the basic raw material cost, the extra manufacturing cost due to the selection of the particular raw material, and the final product quality cost. These costs are systematically simulated for three typical areas of interest: for the purchasing operation, for the manufacturing process and for the final product quality acceptance by the customer.     

Application of knowledge-based artificial immune system (KBAIS) for computer aided process planning in CIM context

In the present era, several manufacturing philosophies like lean manufacturing, total quality management (TQM), etc., have the goal of providing a quality product at reduced cost. In this research paper the process planning problem of a CIM system has been discussed where minimisation of cost of the finished product is considered as the main objective. For determining the cost of the finished product, scrap cost, forgotten by most of the previous researchers, has been considered along with other costs like raw material cost, processing cost, etc. In the present environment of concurrent engineering, optimisation of process planning is an NP-hard problem. To solve this complex problem a noble search algorithm, known as knowledge-based artificial immune system (KBAIS) has been proposed. The nobility of the proposed algorithm is that the inherent capability of AIS has been gleaned and incorporated with the property of the knowledge base. In this problem, the power of knowledge has been used for three stages in the algorithm: initialisation, selection and hyper-mutation. To demonstrate the efficacy of the proposed KBAIS, a bench mark problem has been considered. Intensive computational experiments have also been performed on randomly generated datasets to reveal the supremacy of the proposed algorithm over other existing heuristics.     

Minimising schedule cost via simulation optimisation: an application in pipe manufacturing

We present a method to minimise the cost of batch schedules for a pipe manufacturing facility. The method determines the sequence of production and start date of the batch considering raw material and finished goods holding cost, late delivery cost, and changeover. Our approach is designed to interface to the company's manufacturing execution system, and uses a simplified model of the production line for speed of execution. We demonstrate that methodology results in significant cost savings when compared to existing schedules.     

Distributed product and facility prototyping in extended manufacturing enterprises

In order to reduce the cost at the early product development stages, the planners need methodologies and tools that would allow them to judge upon the implications of the product design on the required manufacturing processes and facilities for their production. This paper reports on a new theoretical platform and a pilot implementation of a decision-making environment for distributed product and facility prototyping in an extended enterprise. The approach is based on an exchange of requests and information between collaborative autonomous agents that support the design, manufacturing planning and facility formation activities. The decision-making is formalized as iterative matching of design, process and facility attributes using multilevel resource capability representation within the extended enterprise. The system is implemented as an XML/CORBA-based environment for conveying design and manufacture messages across traditional technology boundaries. The reported research aims to provide the designers with a rapid manufacturing feasibility assessment tool to be used at different design and planning stages in extended manufacturing enterprises.     

Computer‐aided tolerance synthesis with statistical method and optimization techniques

Most tolerance design optimization problems have focused on developing exact methods to reduce manufacturing cost or to increase product quality. The inherent assumption with this approach is that assembly functions are known before a tolerance design problem is analyzed. With the current development of CAD (Computer‐Aided Design) software, design engineers can address the tolerance design problem without knowing assembly functions in advance. In this study, VSA‐3D/Pro software, which contains a set of simulation tools, is employed to generate experimental assembly data. These computer experimental data will be converted into other forms such as total cost and Process Capability Index. Total cost consists of tolerance cost and quality loss. Then, empirical equations representing two variables can be obtained through a statistical regression method. After that, mathematical optimization and sensitivity analysis are performed within the constrained ‘desired design and process’ space. Consequently, tolerance design via computer experiments enables engineers to optimize design tolerance and manufacturing variation to achieve the highest quality at the most cost effective price during the design and planning stage. Copyright © 2001 John Wiley & Sons, Ltd.     

A graph-based model for manufacturing complexity

This paper presents a graph-based model to measure the relative manufacturing complexity of and the manufacturing similarity of products in job shop manufacturing systems. This model depicts the impact of the complexity factors on the profit realisable from products based on their manufacturing process and required resources/skills. These resources deal with the process required for a component to reach assembly, the process of assembling the components to a whole product. This relative manufacturing complexity measure not only can support assembly and production cost estimation, but also can provide a guideline for creating a product with the most effective balance of manufacturing and assembly. Also, the results of this study can help improve budgeting and resource allocation, and the product life cycle cost estimation for future products. A numerical example is also presented to demonstrate the application of the proposed approach.     

Minimum cost and weight design of fuselage frames: Part B: cost considerations,optimization, and results

An approach is presented to design fuselage frames for minimum weight, minimum cost, or a combination of the two. The approach combines structural requirements and manufacturing constraints into an optimization scheme that alters the geometry of the individual frame components until the objective function is minimized. In addition to the lowest weight and cost points, a near-optimal Pareto set of designs is found, out of which the design that minimizes both cost and weight is determined through a penalty function approach. Four different fabrication processes are considered: conventional sheet metal, high speed machined metal, hand laid-up composite, and resin transfer molded composite. For lightly loaded frames, an automated resin transfer molding process gives the lowest cost and weight designs. For highly loaded frames, high speed machining gives the lowest cost design but automated resin transfer molding gives the lowest weight design. The effects of fabrication process and some of the design and manufacturing constraints on cost and weight are examined.     

Optimal replenishment cycle for perishable items facing demand uncertainty in a two-echelon inventory system

We consider a two-echelon supply chain with an upstream manufacturer and a downstream retailer for a single perishable product. The manufacturer processes raw materials into finished products, which are purchased by the retailer in each replenishment cycle. The raw materials of the manufacturer are highly perishable (i.e. perishing within hours or days), and the finished goods at the retailer face demand uncertainty and obsolescence. We model the manufacturer–retailer relationship as a Stackelberg game where the retailer is the leader and decides the replenishment cycle that minimises its mismatch cost between supply and uncertain demand. The manufacturer is the follower and decides its processing rate to minimise its unit cost for finished goods. Our results show that the raw material and finished goods lifetimes, which are interrelated through the duration of the replenishment cycle, have a significant impact on supply chain costs. Although raw material spoilage cost by itself is low, we show that short raw material lifetimes have a significant impact on the costs of both parties. Additionally, we find that while high manufacturer markups increase retailer costs, they reduce the manufacturer's costs due to large production batches.     

Automated setup planning in CAPP: a modified particle swarm optimisation-based approach

Comprehensive process planning is the key technology for linking design and the manufacturing process and is a rather complex and difficult task. Setup planning has a basic role in computer-aided process planning (CAPP) and significantly affects the overall cost and quality of machined parts. This paper presents a generative system and particle swarm optimisation algorithm (PSO) approach to the setup planning of a given part. The proposed approach and optimisation methodology analyses constraints such as the TAD (tool approach direction), the tolerance relation between features and feature precedence relations, to generate all possible process plans using the workshop resource database. Tolerance relation analysis has a significant impact on setup planning to obtain part accuracy. Based on technological constraints, the PSO algorithm approach, which adopts the feature-based representation, optimises the setup planning using cost indices. To avoid becoming trapped in local optima and to explore the search space extensively, several new operators have been developed to improve the particles’ movements, combined into a modified PSO algorithm. A practical case study is illustrated to demonstrate the effectiveness of the algorithm in optimising the setup planning.     

Process plan selection

Process planning is the task of generating a plan for transforming raw material to its finished form according to design specifications. The existence of alternative feasible process plans for a part and the manufacture of several parts in a single facility sharing constrained resources, makes careful selection of process plans essential. This paper formalizes the selection of process plans with the objective of minimizing the total processing time and the total number of processing steps. The set of plans are then consolidated to minimize the resources used. This is accompanied by intangible benefits such as simplified planning and scheduling, fewer constraints on designing the layout, and an overall reduction in the manufacturing cost. As a word of caution, it may be added that process plans have wide ranging impact on factory operations and it is unrealistic to expect a single model to be comprehensive in addressing the problem. The model outlined in the paper highlights the key issues and provides an analytical basis for selecting process plans.     

Cusp geometry analysis in free-form surface machining

The measurement of cusp height is the conventional method for determining the amount of excess material on free-form machined surfaces, and is frequently used to justify surface quality at the design and manufacturing stages. Although, such surface assessment strategies are generally accepted by manufacturers and customers, they may not provide enough information to qualify the machined surfaces. The aim of this work is to develop a new surface assessment method, for the machined surfaces by determining the area and the volume of the cusps. The method is built on analytic mathematical models of the surfaces and enhanced by the explicit forms of the cusp area and volume equations. The accuracy and reliability of these analytical formulations have been tested with data from machining trials and comparisons with a commerical software package. The indications are that this new approach offers a more comprehensive surface assessment strategy than the conventional measuring method.     

Cost modelling in polymer composite applications: Case study – Analysis of existing and automated manufacturing processes for a large wind turbine blade

Cost modelling is typically one of the first steps in the design and development of a new or existing product and can show clear avenues for effective manufacturing. This paper provides an overview of existing cost modelling techniques and details the process term technical cost modelling (TCM), which is a combined parametric and process flow simulation method used widely throughout the manufacturing industry where historical data is either not available or does not exist. A focus is drawn on the manufacture of a 40 m wind turbine blade with the effects of part size, production volume, materials costs and tooling being detailed. A case study is presented which investigates the cost effectiveness of a range of existing manual production methods (hand-lay prepreg, VI, LRTM) and compares this to automated manufacturing (ATL, AFP, overlay braiding). ATL and AFP are shown to reduce manufacturing costs by up to 8% despite the high capital costs associated with automated equipment. The cost centres are isolated and clearly indicate the dominance of materials and labour. Material deposition in the tool is only one of a string of labour intensive processes in the manufacture of a large wind turbine blades and a holistic automated blade manufacturing approach is perhaps required to see the true labour saving benefits.     

Simultaneous optimal selection of design and manufacturing tolerances with different stack-up conditions using genetic algorithms

Tolerance design is one of the most critical aspects of product design and development process as it affects both the product's functional requirements and manufacturing cost. Unnecessarily tight tolerances lead to increased manufacturing cost, while loose tolerances may lead to malfunctioning of the product. Traditionally, this important phase of product development is accomplished intuitively to satisfy design constraints, based on handbooks' data and/or skill and experience of the designers. Tolerance design carried out in this manner does not necessarily lead to an optimum design. Research in this area indicates that, in general, tolerance design is carried out sequentially in two steps; (1) tolerance design in CAD to obtain design or functional tolerances and (2) tolerance design in CAPP to obtain manufacturing tolerances. Such a sequential approach to tolerance design suffers from several drawbacks, such as more time consumption, suboptimality and unhealthy working atmosphere. This paper reports on an integrated approach for simultaneous selection of design and manufacturing tolerances based on the minimization of the total manufacturing cost. The nonlinear multivariable optimization problem formulated in this manner may result in a noisy solution surface, which can effectively be solved with the help of a global optimization technique. A solution methodology using genetic algorithms and applying penalty function approach with proper normalization of the penalty terms for handling the constraints is proposed. The application of the proposed methodology is demonstrated on a simple mechanical assembly with different tolerance stack-up conditions.     

Integrating the economic production model with deteriorating raw material over multi-production cycles

This paper considers an Economic Production Quantity (EPQ) model with deteriorating raw material and investigates the impact of deterioration on the production process. The EPQ base case with no deterioration is presented where raw material is ordered for multiple production cycles. We present the differential equations to calculate the on-hand inventory of raw material and present closed-forms expressions for the required order of raw material to result in a desired amount of effective raw material per order cycle. Closed-form expression for the total profit per unit time is obtained and we solve for the optimal production quantity of finished product per production cycle and the order quantity of raw material. We present numerical examples where we compare our model to a system which ignores the impact of deterioration and results in shorter production cycles due to an insufficient amount of effective raw material.     

STEP-based automatic system for recognising design and manufacturing features

In the present work, a STEP-based platform-independent system for design and manufacturing feature recognition is developed. A manufacturing feature taxonomy with multiple levels, which is based on the access directions of the feature, is proposed. The system can recognise both design and manufacturing features from the lower level geometry and topology available in the STEP file. The developed system can recognise intersecting features, which is a major shortcoming of previous attempts based on neutral formats. A more complete feature relationship analysis than available in the literature is carried out to find the relationships between all the types of features. Removal volumes and access directions of the features are determined to couple the feature recognition with down line applications. Raw material geometry is also considered while recognising the features. The present system is limited to parts that can be machined on a three-axis machining centre.     

A novel approach to include sustainability concepts in classical DFMA methodology for sheet metal enclosure devices

Nowadays sustainable design is a mandatory requirement in the product development process. For this reason, design methodologies are addressed to establish a close relationship between environmental, social and economic impact indicators and product features from early design stages, especially in those features related to its manufacturing. In this paper, the design for manufacturing and assembly—DFMA methodology is adapted to sheet metal enclosure devices, integrating functional and component relationships to minimize particular sustainability indicators such as energy consumption, carbon footprint, number of parts, required amount of material, assembly time and manufacturing costs. Savings with the proposed method are achieved following specific sub-tasks oriented to define new simplified product components, considering changes in manufacturing processes and re-defining mechanical connections between parts. Traditional DFMA approaches consider manufacturing and assembly issues related to a reduction of product complexity and economic savings. The proposed method aims to examine the benefits in life cycle stages such as raw material consumption, service, maintenance, upgrading and end of life—EOL. The methodology is validated through a redesign of a sheet metal industrial clock, in which the sustainability impacts are calculated from a comparison of an existent product vs. a new product development. The implementation of the method in the case study demonstrate reductions of more than 25% in product mass, consumed energy and CO₂ footprint, and more than 50% in theoretical assembly time and product complexity. Sustainability indicators of the proposed method are selected from literature analysis and taking into account attributes of sheet metal enclosure devices.