Work package 2:
Complexity driver identification, quantification and statistical evaluation
In contrast to OEMs remanufacturing companies can only respond passively to variety: instead of avoiding variety right from the start, they only have the choice between reducing or handling it.
reCORE concentrates its analysis and approach on four target fields: production organization, planning and control, core management and identification. Content of the first work package were the identification, quantification and statistical evaluation of complexity drivers in remanufacturing. The relevant literature distinguishes four complexity dimensions: variety, size, uncertainty and dynamics. Within these four dimensions different drivers cause complexity like number of products, sales market, machine availability etc.
The processing of work package 2 has been closed. The aim of the work package was to generate a database for the sections organisation of production, production planning and scheduling, management of used parts and identification. Every required analysis and development of methods, technical solutions and figures for the project are based on that.
The essential achievements are listed below.
Evaluation of the data entry form
The entry form was needed for the data acquisition in the companies. It showed their current market situation, the structure of the production process and production flow, stock holding, management of used parts and information and identification technologies.
The answers helped to discover the complexity’s drivers and impacts on the remanufacturing companies and at same time the evaluation and weighting of those were made on the basis of those answers.
Process mapping/Data acquisition
Value stream charts have been generated for all visited remanufacturing companies which show the flow of material and the information flow as well as all administrative and operative departments of the company.
They document the collected data and are used for cross-company analysis and process optimisation relating to the four target fields.
Data analysis: cross-references
Using the collected data and data from the companies‘ ERP-systems analysis for cross-references have been made. Cross-references express the correlation between the original item numbers and the in-house item numbers.
New operating figures have been defined based on the analysis of cross-references which had been implemented within the reCORE project:
The frequency of the in-house item numbers ρIT = (1-1IT/XOE) defines how many extern alternatives (OE-numbers) can be represented by one in-house item number. This gives evidence about how efficient the existing spectrum of variants in the company is.
The frequency of the OE-numbers ρOE = (1-1OE/XIT) defines how many in-house item numbers are generated by one OE-number and complements the frequency of the in-house item number explained above during the evaluation of the company.
Identification and quantification of drivers and impacts in the four target fields
The result of work package 2 is a cause-effect matrix which illustrates the causes and impacts of individual complexity drivers in the four target fields (organisation of production, production planning and scheduling, management of used parts and identification). The work package‘s main challenge was to find a method which allows a quantification and thereby a weighting of the drivers and impacts.
At first a modified cause-effect analysis was used to identify complexity drivers and effects in the remanufacturing process. In total 62 drivers and 50 effects were determined. For quantifying these drivers and effects a discrete assessment was made based on expert interviews and process analyses. For each target field in each complexity dimension as well as for each driver the 50 effects were assessed by "1: identified effect applies" and "0: identified effect does not apply".
In the end 4.200 assessed coherences existed which formed the basis for further analyses.
The evaluation showed that complexity in remanufacturing companies causes high internal coordination efforts. Another two important effects of complexity are that the staff work mainly experience based and need broad qualification and skills. Top ranking drivers which cause the effects are core quality, the number of different product groups and also the experience of the employees. The strongest complexity dimension is variety.
The interdependencies between the particular effects were rated based on the results to identify those which were not listed among the top-effects at that time but which were nevertheless of importance.
The described methodology to quantify complexity was applied for the very first time. Even in the field of new manufacturing a comparable method does not exist. Literature about complexity research is rare in general.
Work package 3
Developing methods, technical solutions and key figures
The essential results of the third work package are described in the following.
For finding a solution common methods for optimization of production were investigated and evaluated at first. They were assigned to the categories Avoid, Reduce and Handle and were adjusted to the requirements of remanufacturing where necessary. Hence a method case was built which can be used by remanufacturing companies to select appropriate measures according to the drivers to reduce complexity. The methods and their explanations will be part of the configurator which is currently in development.
Furthermore, the application of the Assemble-to-order (ATO) concept in remanufacturing has been analyzed. The difference of this concept is that a costumer-oriented order does not start with the disassembly of a used part, but only with the assembly. The uncertain processes like disassembly, cleaning and reconditioning are separated from the certain assembly process in this way. So the processing time of an order can be reduced significantly and the costumer receives the ordered product more quickly. The key advantage though is that the diversity of variants can be managed through ATO.
However, the concept implicates disadavantages. When decoupling the assembly from the remaining processes all processes have to be disposed and planned separatly. This demands a higher expenditure of time and personnel. A further disadvantage is the stocking of remolded spare parts at a higher level of added value which implies higher costs.
The analyses showed which additional expenses arise and in which case the application of the concept is suitable for remanufacturing.
Moreover, a new control procedure has been developed according to the needs of the remanufacturers – the remanufacturing orientated control (ROC) as an integrated control model. A centralized order authorization with a decentralized order release and processes which are summarized to separate work systems and which regulate themselves through a decentral capacity leveling are significant for ROC.
Key figures have been developed to measure complexity and the achieved improvements. They will be specified in the following report.
In the section of identification a RFID-demonstrator is built at present. It shows the advantages of auto-ID applications in remanufacturing processes interactively. Improvement measures can be depicted descriptively through the demonstrator. A further advantage is the integrated and automated acquisition and evaluation of manufacturing data. On the basis of the data expenditures, periods, reject rates etc. can be calculated realistically, rather than estimated as usual, and thus a more precise planning of processes and stocks can be made. The structure of the model is to enable an estimation of the needed costs and expenditure of time to implement new identification methods and is also to give information on technical difficulties when adopting RFID-technologies in the remanufacturing setting. The model is built with compenents from fischertechnik® and is completed with purchased RFID- and control hardware. The internal labor consists of developping and programming the process and of generating the actual learning effect.
The described solutions in their unity and their different combinations and configuration gradations are conducive for the methodical generation of firm-specific optimized production configurations for remanufacturing companies.
Figures and slides showing more details